2937 lines
109 KiB
Python
2937 lines
109 KiB
Python
from sympy import Basic, Add, Mul, Pow, degree, Symbol, expand, cancel, Expr, roots
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from sympy.core.containers import Tuple
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from sympy.core.evalf import EvalfMixin, prec_to_dps
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from sympy.core.logic import fuzzy_and
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from sympy.core.numbers import Integer, ComplexInfinity
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from sympy.core.symbol import Dummy
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from sympy.core.sympify import sympify, _sympify
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from sympy.polys import Poly, rootof
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from sympy.series import limit
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from sympy.matrices import ImmutableMatrix, eye
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from sympy.matrices.expressions import MatMul, MatAdd
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__all__ = ['TransferFunction', 'Series', 'MIMOSeries', 'Parallel', 'MIMOParallel',
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'Feedback', 'MIMOFeedback', 'TransferFunctionMatrix']
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def _roots(poly, var):
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""" like roots, but works on higher-order polynomials. """
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r = roots(poly, var, multiple=True)
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n = degree(poly)
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if len(r) != n:
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r = [rootof(poly, var, k) for k in range(n)]
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return r
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class LinearTimeInvariant(Basic, EvalfMixin):
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"""A common class for all the Linear Time-Invariant Dynamical Systems."""
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# Users should not directly interact with this class.
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def __new__(cls, *system, **kwargs):
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if cls is LinearTimeInvariant:
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raise NotImplementedError('The LTICommon class is not meant to be used directly.')
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return super(LinearTimeInvariant, cls).__new__(cls, *system, **kwargs)
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@classmethod
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def _check_args(cls, args):
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if not args:
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raise ValueError("Atleast 1 argument must be passed.")
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if not all(isinstance(arg, cls._clstype) for arg in args):
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raise TypeError(f"All arguments must be of type {cls._clstype}.")
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var_set = {arg.var for arg in args}
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if len(var_set) != 1:
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raise ValueError("All transfer functions should use the same complex variable"
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f" of the Laplace transform. {len(var_set)} different values found.")
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@property
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def is_SISO(self):
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"""Returns `True` if the passed LTI system is SISO else returns False."""
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return self._is_SISO
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class SISOLinearTimeInvariant(LinearTimeInvariant):
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"""A common class for all the SISO Linear Time-Invariant Dynamical Systems."""
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# Users should not directly interact with this class.
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_is_SISO = True
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class MIMOLinearTimeInvariant(LinearTimeInvariant):
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"""A common class for all the MIMO Linear Time-Invariant Dynamical Systems."""
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# Users should not directly interact with this class.
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_is_SISO = False
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SISOLinearTimeInvariant._clstype = SISOLinearTimeInvariant
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MIMOLinearTimeInvariant._clstype = MIMOLinearTimeInvariant
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def _check_other_SISO(func):
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def wrapper(*args, **kwargs):
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if not isinstance(args[-1], SISOLinearTimeInvariant):
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return NotImplemented
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else:
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return func(*args, **kwargs)
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return wrapper
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def _check_other_MIMO(func):
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def wrapper(*args, **kwargs):
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if not isinstance(args[-1], MIMOLinearTimeInvariant):
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return NotImplemented
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else:
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return func(*args, **kwargs)
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return wrapper
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class TransferFunction(SISOLinearTimeInvariant):
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r"""
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A class for representing LTI (Linear, time-invariant) systems that can be strictly described
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by ratio of polynomials in the Laplace transform complex variable. The arguments
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are ``num``, ``den``, and ``var``, where ``num`` and ``den`` are numerator and
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denominator polynomials of the ``TransferFunction`` respectively, and the third argument is
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a complex variable of the Laplace transform used by these polynomials of the transfer function.
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``num`` and ``den`` can be either polynomials or numbers, whereas ``var``
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has to be a Symbol.
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Explanation
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===========
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Generally, a dynamical system representing a physical model can be described in terms of Linear
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Ordinary Differential Equations like -
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$\small{b_{m}y^{\left(m\right)}+b_{m-1}y^{\left(m-1\right)}+\dots+b_{1}y^{\left(1\right)}+b_{0}y=
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a_{n}x^{\left(n\right)}+a_{n-1}x^{\left(n-1\right)}+\dots+a_{1}x^{\left(1\right)}+a_{0}x}$
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Here, $x$ is the input signal and $y$ is the output signal and superscript on both is the order of derivative
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(not exponent). Derivative is taken with respect to the independent variable, $t$. Also, generally $m$ is greater
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than $n$.
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It is not feasible to analyse the properties of such systems in their native form therefore, we use
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mathematical tools like Laplace transform to get a better perspective. Taking the Laplace transform
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of both the sides in the equation (at zero initial conditions), we get -
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$\small{\mathcal{L}[b_{m}y^{\left(m\right)}+b_{m-1}y^{\left(m-1\right)}+\dots+b_{1}y^{\left(1\right)}+b_{0}y]=
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\mathcal{L}[a_{n}x^{\left(n\right)}+a_{n-1}x^{\left(n-1\right)}+\dots+a_{1}x^{\left(1\right)}+a_{0}x]}$
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Using the linearity property of Laplace transform and also considering zero initial conditions
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(i.e. $\small{y(0^{-}) = 0}$, $\small{y'(0^{-}) = 0}$ and so on), the equation
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above gets translated to -
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$\small{b_{m}\mathcal{L}[y^{\left(m\right)}]+\dots+b_{1}\mathcal{L}[y^{\left(1\right)}]+b_{0}\mathcal{L}[y]=
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a_{n}\mathcal{L}[x^{\left(n\right)}]+\dots+a_{1}\mathcal{L}[x^{\left(1\right)}]+a_{0}\mathcal{L}[x]}$
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Now, applying Derivative property of Laplace transform,
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$\small{b_{m}s^{m}\mathcal{L}[y]+\dots+b_{1}s\mathcal{L}[y]+b_{0}\mathcal{L}[y]=
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a_{n}s^{n}\mathcal{L}[x]+\dots+a_{1}s\mathcal{L}[x]+a_{0}\mathcal{L}[x]}$
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Here, the superscript on $s$ is **exponent**. Note that the zero initial conditions assumption, mentioned above, is very important
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and cannot be ignored otherwise the dynamical system cannot be considered time-independent and the simplified equation above
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cannot be reached.
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Collecting $\mathcal{L}[y]$ and $\mathcal{L}[x]$ terms from both the sides and taking the ratio
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$\frac{ \mathcal{L}\left\{y\right\} }{ \mathcal{L}\left\{x\right\} }$, we get the typical rational form of transfer
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function.
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The numerator of the transfer function is, therefore, the Laplace transform of the output signal
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(The signals are represented as functions of time) and similarly, the denominator
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of the transfer function is the Laplace transform of the input signal. It is also a convention
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to denote the input and output signal's Laplace transform with capital alphabets like shown below.
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$H(s) = \frac{Y(s)}{X(s)} = \frac{ \mathcal{L}\left\{y(t)\right\} }{ \mathcal{L}\left\{x(t)\right\} }$
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$s$, also known as complex frequency, is a complex variable in the Laplace domain. It corresponds to the
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equivalent variable $t$, in the time domain. Transfer functions are sometimes also referred to as the Laplace
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transform of the system's impulse response. Transfer function, $H$, is represented as a rational
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function in $s$ like,
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$H(s) =\ \frac{a_{n}s^{n}+a_{n-1}s^{n-1}+\dots+a_{1}s+a_{0}}{b_{m}s^{m}+b_{m-1}s^{m-1}+\dots+b_{1}s+b_{0}}$
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Parameters
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==========
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num : Expr, Number
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The numerator polynomial of the transfer function.
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den : Expr, Number
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The denominator polynomial of the transfer function.
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var : Symbol
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Complex variable of the Laplace transform used by the
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polynomials of the transfer function.
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Raises
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======
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TypeError
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When ``var`` is not a Symbol or when ``num`` or ``den`` is not a
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number or a polynomial.
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ValueError
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When ``den`` is zero.
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Examples
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========
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>>> from sympy.abc import s, p, a
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>>> from sympy.physics.control.lti import TransferFunction
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>>> tf1 = TransferFunction(s + a, s**2 + s + 1, s)
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>>> tf1
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TransferFunction(a + s, s**2 + s + 1, s)
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>>> tf1.num
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a + s
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>>> tf1.den
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s**2 + s + 1
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>>> tf1.var
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s
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>>> tf1.args
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(a + s, s**2 + s + 1, s)
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Any complex variable can be used for ``var``.
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>>> tf2 = TransferFunction(a*p**3 - a*p**2 + s*p, p + a**2, p)
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>>> tf2
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TransferFunction(a*p**3 - a*p**2 + p*s, a**2 + p, p)
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>>> tf3 = TransferFunction((p + 3)*(p - 1), (p - 1)*(p + 5), p)
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>>> tf3
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TransferFunction((p - 1)*(p + 3), (p - 1)*(p + 5), p)
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To negate a transfer function the ``-`` operator can be prepended:
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>>> tf4 = TransferFunction(-a + s, p**2 + s, p)
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>>> -tf4
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TransferFunction(a - s, p**2 + s, p)
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>>> tf5 = TransferFunction(s**4 - 2*s**3 + 5*s + 4, s + 4, s)
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>>> -tf5
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TransferFunction(-s**4 + 2*s**3 - 5*s - 4, s + 4, s)
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You can use a Float or an Integer (or other constants) as numerator and denominator:
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>>> tf6 = TransferFunction(1/2, 4, s)
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>>> tf6.num
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0.500000000000000
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>>> tf6.den
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4
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>>> tf6.var
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s
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>>> tf6.args
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(0.5, 4, s)
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You can take the integer power of a transfer function using the ``**`` operator:
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>>> tf7 = TransferFunction(s + a, s - a, s)
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>>> tf7**3
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TransferFunction((a + s)**3, (-a + s)**3, s)
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>>> tf7**0
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TransferFunction(1, 1, s)
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>>> tf8 = TransferFunction(p + 4, p - 3, p)
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>>> tf8**-1
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TransferFunction(p - 3, p + 4, p)
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Addition, subtraction, and multiplication of transfer functions can form
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unevaluated ``Series`` or ``Parallel`` objects.
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>>> tf9 = TransferFunction(s + 1, s**2 + s + 1, s)
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>>> tf10 = TransferFunction(s - p, s + 3, s)
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>>> tf11 = TransferFunction(4*s**2 + 2*s - 4, s - 1, s)
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>>> tf12 = TransferFunction(1 - s, s**2 + 4, s)
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>>> tf9 + tf10
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Parallel(TransferFunction(s + 1, s**2 + s + 1, s), TransferFunction(-p + s, s + 3, s))
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>>> tf10 - tf11
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Parallel(TransferFunction(-p + s, s + 3, s), TransferFunction(-4*s**2 - 2*s + 4, s - 1, s))
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>>> tf9 * tf10
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Series(TransferFunction(s + 1, s**2 + s + 1, s), TransferFunction(-p + s, s + 3, s))
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>>> tf10 - (tf9 + tf12)
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Parallel(TransferFunction(-p + s, s + 3, s), TransferFunction(-s - 1, s**2 + s + 1, s), TransferFunction(s - 1, s**2 + 4, s))
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>>> tf10 - (tf9 * tf12)
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Parallel(TransferFunction(-p + s, s + 3, s), Series(TransferFunction(-1, 1, s), TransferFunction(s + 1, s**2 + s + 1, s), TransferFunction(1 - s, s**2 + 4, s)))
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>>> tf11 * tf10 * tf9
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Series(TransferFunction(4*s**2 + 2*s - 4, s - 1, s), TransferFunction(-p + s, s + 3, s), TransferFunction(s + 1, s**2 + s + 1, s))
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>>> tf9 * tf11 + tf10 * tf12
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Parallel(Series(TransferFunction(s + 1, s**2 + s + 1, s), TransferFunction(4*s**2 + 2*s - 4, s - 1, s)), Series(TransferFunction(-p + s, s + 3, s), TransferFunction(1 - s, s**2 + 4, s)))
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>>> (tf9 + tf12) * (tf10 + tf11)
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Series(Parallel(TransferFunction(s + 1, s**2 + s + 1, s), TransferFunction(1 - s, s**2 + 4, s)), Parallel(TransferFunction(-p + s, s + 3, s), TransferFunction(4*s**2 + 2*s - 4, s - 1, s)))
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These unevaluated ``Series`` or ``Parallel`` objects can convert into the
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resultant transfer function using ``.doit()`` method or by ``.rewrite(TransferFunction)``.
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>>> ((tf9 + tf10) * tf12).doit()
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TransferFunction((1 - s)*((-p + s)*(s**2 + s + 1) + (s + 1)*(s + 3)), (s + 3)*(s**2 + 4)*(s**2 + s + 1), s)
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>>> (tf9 * tf10 - tf11 * tf12).rewrite(TransferFunction)
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TransferFunction(-(1 - s)*(s + 3)*(s**2 + s + 1)*(4*s**2 + 2*s - 4) + (-p + s)*(s - 1)*(s + 1)*(s**2 + 4), (s - 1)*(s + 3)*(s**2 + 4)*(s**2 + s + 1), s)
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See Also
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========
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Feedback, Series, Parallel
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References
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==========
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.. [1] https://en.wikipedia.org/wiki/Transfer_function
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.. [2] https://en.wikipedia.org/wiki/Laplace_transform
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"""
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def __new__(cls, num, den, var):
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num, den = _sympify(num), _sympify(den)
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if not isinstance(var, Symbol):
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raise TypeError("Variable input must be a Symbol.")
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if den == 0:
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raise ValueError("TransferFunction can't have a zero denominator.")
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if (((isinstance(num, Expr) and num.has(Symbol)) or num.is_number) and
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((isinstance(den, Expr) and den.has(Symbol)) or den.is_number)):
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obj = super(TransferFunction, cls).__new__(cls, num, den, var)
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obj._num = num
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obj._den = den
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obj._var = var
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return obj
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else:
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raise TypeError("Unsupported type for numerator or denominator of TransferFunction.")
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@classmethod
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def from_rational_expression(cls, expr, var=None):
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r"""
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Creates a new ``TransferFunction`` efficiently from a rational expression.
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Parameters
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==========
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expr : Expr, Number
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The rational expression representing the ``TransferFunction``.
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var : Symbol, optional
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Complex variable of the Laplace transform used by the
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polynomials of the transfer function.
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Raises
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======
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ValueError
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When ``expr`` is of type ``Number`` and optional parameter ``var``
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is not passed.
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When ``expr`` has more than one variables and an optional parameter
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``var`` is not passed.
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ZeroDivisionError
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When denominator of ``expr`` is zero or it has ``ComplexInfinity``
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in its numerator.
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Examples
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========
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>>> from sympy.abc import s, p, a
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>>> from sympy.physics.control.lti import TransferFunction
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>>> expr1 = (s + 5)/(3*s**2 + 2*s + 1)
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>>> tf1 = TransferFunction.from_rational_expression(expr1)
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>>> tf1
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TransferFunction(s + 5, 3*s**2 + 2*s + 1, s)
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>>> expr2 = (a*p**3 - a*p**2 + s*p)/(p + a**2) # Expr with more than one variables
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>>> tf2 = TransferFunction.from_rational_expression(expr2, p)
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>>> tf2
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TransferFunction(a*p**3 - a*p**2 + p*s, a**2 + p, p)
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In case of conflict between two or more variables in a expression, SymPy will
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raise a ``ValueError``, if ``var`` is not passed by the user.
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>>> tf = TransferFunction.from_rational_expression((a + a*s)/(s**2 + s + 1))
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Traceback (most recent call last):
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...
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ValueError: Conflicting values found for positional argument `var` ({a, s}). Specify it manually.
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This can be corrected by specifying the ``var`` parameter manually.
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>>> tf = TransferFunction.from_rational_expression((a + a*s)/(s**2 + s + 1), s)
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>>> tf
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TransferFunction(a*s + a, s**2 + s + 1, s)
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``var`` also need to be specified when ``expr`` is a ``Number``
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>>> tf3 = TransferFunction.from_rational_expression(10, s)
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>>> tf3
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TransferFunction(10, 1, s)
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"""
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expr = _sympify(expr)
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if var is None:
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_free_symbols = expr.free_symbols
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_len_free_symbols = len(_free_symbols)
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if _len_free_symbols == 1:
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var = list(_free_symbols)[0]
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elif _len_free_symbols == 0:
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raise ValueError("Positional argument `var` not found in the TransferFunction defined. Specify it manually.")
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else:
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raise ValueError("Conflicting values found for positional argument `var` ({}). Specify it manually.".format(_free_symbols))
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_num, _den = expr.as_numer_denom()
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if _den == 0 or _num.has(ComplexInfinity):
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raise ZeroDivisionError("TransferFunction can't have a zero denominator.")
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return cls(_num, _den, var)
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@property
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def num(self):
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"""
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Returns the numerator polynomial of the transfer function.
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Examples
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========
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>>> from sympy.abc import s, p
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>>> from sympy.physics.control.lti import TransferFunction
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>>> G1 = TransferFunction(s**2 + p*s + 3, s - 4, s)
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>>> G1.num
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p*s + s**2 + 3
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>>> G2 = TransferFunction((p + 5)*(p - 3), (p - 3)*(p + 1), p)
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>>> G2.num
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(p - 3)*(p + 5)
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"""
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return self._num
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@property
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def den(self):
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"""
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Returns the denominator polynomial of the transfer function.
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Examples
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========
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>>> from sympy.abc import s, p
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>>> from sympy.physics.control.lti import TransferFunction
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>>> G1 = TransferFunction(s + 4, p**3 - 2*p + 4, s)
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>>> G1.den
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p**3 - 2*p + 4
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>>> G2 = TransferFunction(3, 4, s)
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>>> G2.den
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4
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"""
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return self._den
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@property
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def var(self):
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"""
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Returns the complex variable of the Laplace transform used by the polynomials of
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the transfer function.
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Examples
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========
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>>> from sympy.abc import s, p
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>>> from sympy.physics.control.lti import TransferFunction
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>>> G1 = TransferFunction(p**2 + 2*p + 4, p - 6, p)
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>>> G1.var
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p
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>>> G2 = TransferFunction(0, s - 5, s)
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>>> G2.var
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s
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"""
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return self._var
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def _eval_subs(self, old, new):
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arg_num = self.num.subs(old, new)
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arg_den = self.den.subs(old, new)
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argnew = TransferFunction(arg_num, arg_den, self.var)
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return self if old == self.var else argnew
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def _eval_evalf(self, prec):
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return TransferFunction(
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self.num._eval_evalf(prec),
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self.den._eval_evalf(prec),
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self.var)
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def _eval_simplify(self, **kwargs):
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tf = cancel(Mul(self.num, 1/self.den, evaluate=False), expand=False).as_numer_denom()
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num_, den_ = tf[0], tf[1]
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return TransferFunction(num_, den_, self.var)
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def expand(self):
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"""
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Returns the transfer function with numerator and denominator
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in expanded form.
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Examples
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========
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>>> from sympy.abc import s, p, a, b
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>>> from sympy.physics.control.lti import TransferFunction
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>>> G1 = TransferFunction((a - s)**2, (s**2 + a)**2, s)
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>>> G1.expand()
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TransferFunction(a**2 - 2*a*s + s**2, a**2 + 2*a*s**2 + s**4, s)
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>>> G2 = TransferFunction((p + 3*b)*(p - b), (p - b)*(p + 2*b), p)
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>>> G2.expand()
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TransferFunction(-3*b**2 + 2*b*p + p**2, -2*b**2 + b*p + p**2, p)
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"""
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return TransferFunction(expand(self.num), expand(self.den), self.var)
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def dc_gain(self):
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"""
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Computes the gain of the response as the frequency approaches zero.
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The DC gain is infinite for systems with pure integrators.
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Examples
|
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========
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|
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>>> from sympy.abc import s, p, a, b
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>>> from sympy.physics.control.lti import TransferFunction
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>>> tf1 = TransferFunction(s + 3, s**2 - 9, s)
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>>> tf1.dc_gain()
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-1/3
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>>> tf2 = TransferFunction(p**2, p - 3 + p**3, p)
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>>> tf2.dc_gain()
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0
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>>> tf3 = TransferFunction(a*p**2 - b, s + b, s)
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>>> tf3.dc_gain()
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(a*p**2 - b)/b
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>>> tf4 = TransferFunction(1, s, s)
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>>> tf4.dc_gain()
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oo
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"""
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m = Mul(self.num, Pow(self.den, -1, evaluate=False), evaluate=False)
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return limit(m, self.var, 0)
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def poles(self):
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"""
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Returns the poles of a transfer function.
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Examples
|
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========
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|
|
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>>> from sympy.abc import s, p, a
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>>> from sympy.physics.control.lti import TransferFunction
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>>> tf1 = TransferFunction((p + 3)*(p - 1), (p - 1)*(p + 5), p)
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>>> tf1.poles()
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[-5, 1]
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>>> tf2 = TransferFunction((1 - s)**2, (s**2 + 1)**2, s)
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>>> tf2.poles()
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[I, I, -I, -I]
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>>> tf3 = TransferFunction(s**2, a*s + p, s)
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>>> tf3.poles()
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[-p/a]
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"""
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return _roots(Poly(self.den, self.var), self.var)
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def zeros(self):
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"""
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Returns the zeros of a transfer function.
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Examples
|
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========
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|
|
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>>> from sympy.abc import s, p, a
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>>> from sympy.physics.control.lti import TransferFunction
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>>> tf1 = TransferFunction((p + 3)*(p - 1), (p - 1)*(p + 5), p)
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>>> tf1.zeros()
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[-3, 1]
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>>> tf2 = TransferFunction((1 - s)**2, (s**2 + 1)**2, s)
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>>> tf2.zeros()
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[1, 1]
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>>> tf3 = TransferFunction(s**2, a*s + p, s)
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>>> tf3.zeros()
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[0, 0]
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"""
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return _roots(Poly(self.num, self.var), self.var)
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def is_stable(self):
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"""
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Returns True if the transfer function is asymptotically stable; else False.
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This would not check the marginal or conditional stability of the system.
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Examples
|
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========
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>>> from sympy.abc import s, p, a
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>>> from sympy import symbols
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>>> from sympy.physics.control.lti import TransferFunction
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>>> q, r = symbols('q, r', negative=True)
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>>> tf1 = TransferFunction((1 - s)**2, (s + 1)**2, s)
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>>> tf1.is_stable()
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True
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>>> tf2 = TransferFunction((1 - p)**2, (s**2 + 1)**2, s)
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>>> tf2.is_stable()
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False
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>>> tf3 = TransferFunction(4, q*s - r, s)
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>>> tf3.is_stable()
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False
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>>> tf4 = TransferFunction(p + 1, a*p - s**2, p)
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>>> tf4.is_stable() is None # Not enough info about the symbols to determine stability
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True
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"""
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return fuzzy_and(pole.as_real_imag()[0].is_negative for pole in self.poles())
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def __add__(self, other):
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if isinstance(other, (TransferFunction, Series)):
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if not self.var == other.var:
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raise ValueError("All the transfer functions should use the same complex variable "
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"of the Laplace transform.")
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return Parallel(self, other)
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elif isinstance(other, Parallel):
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if not self.var == other.var:
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raise ValueError("All the transfer functions should use the same complex variable "
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"of the Laplace transform.")
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arg_list = list(other.args)
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return Parallel(self, *arg_list)
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else:
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raise ValueError("TransferFunction cannot be added with {}.".
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format(type(other)))
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def __radd__(self, other):
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return self + other
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def __sub__(self, other):
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if isinstance(other, (TransferFunction, Series)):
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if not self.var == other.var:
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raise ValueError("All the transfer functions should use the same complex variable "
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"of the Laplace transform.")
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return Parallel(self, -other)
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elif isinstance(other, Parallel):
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if not self.var == other.var:
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raise ValueError("All the transfer functions should use the same complex variable "
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"of the Laplace transform.")
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arg_list = [-i for i in list(other.args)]
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return Parallel(self, *arg_list)
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else:
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raise ValueError("{} cannot be subtracted from a TransferFunction."
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.format(type(other)))
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def __rsub__(self, other):
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return -self + other
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def __mul__(self, other):
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if isinstance(other, (TransferFunction, Parallel)):
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if not self.var == other.var:
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raise ValueError("All the transfer functions should use the same complex variable "
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"of the Laplace transform.")
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return Series(self, other)
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elif isinstance(other, Series):
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if not self.var == other.var:
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raise ValueError("All the transfer functions should use the same complex variable "
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"of the Laplace transform.")
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arg_list = list(other.args)
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return Series(self, *arg_list)
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else:
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raise ValueError("TransferFunction cannot be multiplied with {}."
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.format(type(other)))
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__rmul__ = __mul__
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def __truediv__(self, other):
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if (isinstance(other, Parallel) and len(other.args) == 2 and isinstance(other.args[0], TransferFunction)
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and isinstance(other.args[1], (Series, TransferFunction))):
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if not self.var == other.var:
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raise ValueError("Both TransferFunction and Parallel should use the"
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" same complex variable of the Laplace transform.")
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if other.args[1] == self:
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# plant and controller with unit feedback.
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return Feedback(self, other.args[0])
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other_arg_list = list(other.args[1].args) if isinstance(other.args[1], Series) else other.args[1]
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if other_arg_list == other.args[1]:
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return Feedback(self, other_arg_list)
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elif self in other_arg_list:
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other_arg_list.remove(self)
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else:
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return Feedback(self, Series(*other_arg_list))
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if len(other_arg_list) == 1:
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return Feedback(self, *other_arg_list)
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else:
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return Feedback(self, Series(*other_arg_list))
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else:
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raise ValueError("TransferFunction cannot be divided by {}.".
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format(type(other)))
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__rtruediv__ = __truediv__
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def __pow__(self, p):
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p = sympify(p)
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if not isinstance(p, Integer):
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raise ValueError("Exponent must be an Integer.")
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if p == 0:
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return TransferFunction(1, 1, self.var)
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elif p > 0:
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num_, den_ = self.num**p, self.den**p
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else:
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p = abs(p)
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num_, den_ = self.den**p, self.num**p
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return TransferFunction(num_, den_, self.var)
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def __neg__(self):
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return TransferFunction(-self.num, self.den, self.var)
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@property
|
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def is_proper(self):
|
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"""
|
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Returns True if degree of the numerator polynomial is less than
|
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or equal to degree of the denominator polynomial, else False.
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Examples
|
|
========
|
|
|
|
>>> from sympy.abc import s, p, a, b
|
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>>> from sympy.physics.control.lti import TransferFunction
|
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>>> tf1 = TransferFunction(b*s**2 + p**2 - a*p + s, b - p**2, s)
|
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>>> tf1.is_proper
|
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False
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>>> tf2 = TransferFunction(p**2 - 4*p, p**3 + 3*p + 2, p)
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>>> tf2.is_proper
|
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True
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"""
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return degree(self.num, self.var) <= degree(self.den, self.var)
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@property
|
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def is_strictly_proper(self):
|
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"""
|
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Returns True if degree of the numerator polynomial is strictly less
|
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than degree of the denominator polynomial, else False.
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|
|
Examples
|
|
========
|
|
|
|
>>> from sympy.abc import s, p, a, b
|
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>>> from sympy.physics.control.lti import TransferFunction
|
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>>> tf1 = TransferFunction(a*p**2 + b*s, s - p, s)
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>>> tf1.is_strictly_proper
|
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False
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>>> tf2 = TransferFunction(s**3 - 2, s**4 + 5*s + 6, s)
|
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>>> tf2.is_strictly_proper
|
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True
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"""
|
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return degree(self.num, self.var) < degree(self.den, self.var)
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@property
|
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def is_biproper(self):
|
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"""
|
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Returns True if degree of the numerator polynomial is equal to
|
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degree of the denominator polynomial, else False.
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|
|
Examples
|
|
========
|
|
|
|
>>> from sympy.abc import s, p, a, b
|
|
>>> from sympy.physics.control.lti import TransferFunction
|
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>>> tf1 = TransferFunction(a*p**2 + b*s, s - p, s)
|
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>>> tf1.is_biproper
|
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True
|
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>>> tf2 = TransferFunction(p**2, p + a, p)
|
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>>> tf2.is_biproper
|
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False
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"""
|
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return degree(self.num, self.var) == degree(self.den, self.var)
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def to_expr(self):
|
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"""
|
|
Converts a ``TransferFunction`` object to SymPy Expr.
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|
|
Examples
|
|
========
|
|
|
|
>>> from sympy.abc import s, p, a, b
|
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>>> from sympy.physics.control.lti import TransferFunction
|
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>>> from sympy import Expr
|
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>>> tf1 = TransferFunction(s, a*s**2 + 1, s)
|
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>>> tf1.to_expr()
|
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s/(a*s**2 + 1)
|
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>>> isinstance(_, Expr)
|
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True
|
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>>> tf2 = TransferFunction(1, (p + 3*b)*(b - p), p)
|
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>>> tf2.to_expr()
|
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1/((b - p)*(3*b + p))
|
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>>> tf3 = TransferFunction((s - 2)*(s - 3), (s - 1)*(s - 2)*(s - 3), s)
|
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>>> tf3.to_expr()
|
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((s - 3)*(s - 2))/(((s - 3)*(s - 2)*(s - 1)))
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|
|
|
"""
|
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|
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if self.num != 1:
|
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return Mul(self.num, Pow(self.den, -1, evaluate=False), evaluate=False)
|
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else:
|
|
return Pow(self.den, -1, evaluate=False)
|
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|
|
|
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def _flatten_args(args, _cls):
|
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temp_args = []
|
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for arg in args:
|
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if isinstance(arg, _cls):
|
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temp_args.extend(arg.args)
|
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else:
|
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temp_args.append(arg)
|
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return tuple(temp_args)
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|
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|
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def _dummify_args(_arg, var):
|
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dummy_dict = {}
|
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dummy_arg_list = []
|
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|
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for arg in _arg:
|
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_s = Dummy()
|
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dummy_dict[_s] = var
|
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dummy_arg = arg.subs({var: _s})
|
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dummy_arg_list.append(dummy_arg)
|
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|
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return dummy_arg_list, dummy_dict
|
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|
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|
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class Series(SISOLinearTimeInvariant):
|
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r"""
|
|
A class for representing a series configuration of SISO systems.
|
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|
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Parameters
|
|
==========
|
|
|
|
args : SISOLinearTimeInvariant
|
|
SISO systems in a series configuration.
|
|
evaluate : Boolean, Keyword
|
|
When passed ``True``, returns the equivalent
|
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``Series(*args).doit()``. Set to ``False`` by default.
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|
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Raises
|
|
======
|
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|
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ValueError
|
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When no argument is passed.
|
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|
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``var`` attribute is not same for every system.
|
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TypeError
|
|
Any of the passed ``*args`` has unsupported type
|
|
|
|
A combination of SISO and MIMO systems is
|
|
passed. There should be homogeneity in the
|
|
type of systems passed, SISO in this case.
|
|
|
|
Examples
|
|
========
|
|
|
|
>>> from sympy.abc import s, p, a, b
|
|
>>> from sympy.physics.control.lti import TransferFunction, Series, Parallel
|
|
>>> tf1 = TransferFunction(a*p**2 + b*s, s - p, s)
|
|
>>> tf2 = TransferFunction(s**3 - 2, s**4 + 5*s + 6, s)
|
|
>>> tf3 = TransferFunction(p**2, p + s, s)
|
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>>> S1 = Series(tf1, tf2)
|
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>>> S1
|
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Series(TransferFunction(a*p**2 + b*s, -p + s, s), TransferFunction(s**3 - 2, s**4 + 5*s + 6, s))
|
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>>> S1.var
|
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s
|
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>>> S2 = Series(tf2, Parallel(tf3, -tf1))
|
|
>>> S2
|
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Series(TransferFunction(s**3 - 2, s**4 + 5*s + 6, s), Parallel(TransferFunction(p**2, p + s, s), TransferFunction(-a*p**2 - b*s, -p + s, s)))
|
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>>> S2.var
|
|
s
|
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>>> S3 = Series(Parallel(tf1, tf2), Parallel(tf2, tf3))
|
|
>>> S3
|
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Series(Parallel(TransferFunction(a*p**2 + b*s, -p + s, s), TransferFunction(s**3 - 2, s**4 + 5*s + 6, s)), Parallel(TransferFunction(s**3 - 2, s**4 + 5*s + 6, s), TransferFunction(p**2, p + s, s)))
|
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>>> S3.var
|
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s
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|
|
You can get the resultant transfer function by using ``.doit()`` method:
|
|
|
|
>>> S3 = Series(tf1, tf2, -tf3)
|
|
>>> S3.doit()
|
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TransferFunction(-p**2*(s**3 - 2)*(a*p**2 + b*s), (-p + s)*(p + s)*(s**4 + 5*s + 6), s)
|
|
>>> S4 = Series(tf2, Parallel(tf1, -tf3))
|
|
>>> S4.doit()
|
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TransferFunction((s**3 - 2)*(-p**2*(-p + s) + (p + s)*(a*p**2 + b*s)), (-p + s)*(p + s)*(s**4 + 5*s + 6), s)
|
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|
|
Notes
|
|
=====
|
|
|
|
All the transfer functions should use the same complex variable
|
|
``var`` of the Laplace transform.
|
|
|
|
See Also
|
|
========
|
|
|
|
MIMOSeries, Parallel, TransferFunction, Feedback
|
|
|
|
"""
|
|
def __new__(cls, *args, evaluate=False):
|
|
|
|
args = _flatten_args(args, Series)
|
|
cls._check_args(args)
|
|
obj = super().__new__(cls, *args)
|
|
|
|
return obj.doit() if evaluate else obj
|
|
|
|
@property
|
|
def var(self):
|
|
"""
|
|
Returns the complex variable used by all the transfer functions.
|
|
|
|
Examples
|
|
========
|
|
|
|
>>> from sympy.abc import p
|
|
>>> from sympy.physics.control.lti import TransferFunction, Series, Parallel
|
|
>>> G1 = TransferFunction(p**2 + 2*p + 4, p - 6, p)
|
|
>>> G2 = TransferFunction(p, 4 - p, p)
|
|
>>> G3 = TransferFunction(0, p**4 - 1, p)
|
|
>>> Series(G1, G2).var
|
|
p
|
|
>>> Series(-G3, Parallel(G1, G2)).var
|
|
p
|
|
|
|
"""
|
|
return self.args[0].var
|
|
|
|
def doit(self, **kwargs):
|
|
"""
|
|
Returns the resultant transfer function obtained after evaluating
|
|
the transfer functions in series configuration.
|
|
|
|
Examples
|
|
========
|
|
|
|
>>> from sympy.abc import s, p, a, b
|
|
>>> from sympy.physics.control.lti import TransferFunction, Series
|
|
>>> tf1 = TransferFunction(a*p**2 + b*s, s - p, s)
|
|
>>> tf2 = TransferFunction(s**3 - 2, s**4 + 5*s + 6, s)
|
|
>>> Series(tf2, tf1).doit()
|
|
TransferFunction((s**3 - 2)*(a*p**2 + b*s), (-p + s)*(s**4 + 5*s + 6), s)
|
|
>>> Series(-tf1, -tf2).doit()
|
|
TransferFunction((2 - s**3)*(-a*p**2 - b*s), (-p + s)*(s**4 + 5*s + 6), s)
|
|
|
|
"""
|
|
|
|
_num_arg = (arg.doit().num for arg in self.args)
|
|
_den_arg = (arg.doit().den for arg in self.args)
|
|
res_num = Mul(*_num_arg, evaluate=True)
|
|
res_den = Mul(*_den_arg, evaluate=True)
|
|
return TransferFunction(res_num, res_den, self.var)
|
|
|
|
def _eval_rewrite_as_TransferFunction(self, *args, **kwargs):
|
|
return self.doit()
|
|
|
|
@_check_other_SISO
|
|
def __add__(self, other):
|
|
|
|
if isinstance(other, Parallel):
|
|
arg_list = list(other.args)
|
|
return Parallel(self, *arg_list)
|
|
|
|
return Parallel(self, other)
|
|
|
|
__radd__ = __add__
|
|
|
|
@_check_other_SISO
|
|
def __sub__(self, other):
|
|
return self + (-other)
|
|
|
|
def __rsub__(self, other):
|
|
return -self + other
|
|
|
|
@_check_other_SISO
|
|
def __mul__(self, other):
|
|
|
|
arg_list = list(self.args)
|
|
return Series(*arg_list, other)
|
|
|
|
def __truediv__(self, other):
|
|
if (isinstance(other, Parallel) and len(other.args) == 2
|
|
and isinstance(other.args[0], TransferFunction) and isinstance(other.args[1], Series)):
|
|
|
|
if not self.var == other.var:
|
|
raise ValueError("All the transfer functions should use the same complex variable "
|
|
"of the Laplace transform.")
|
|
self_arg_list = set(list(self.args))
|
|
other_arg_list = set(list(other.args[1].args))
|
|
res = list(self_arg_list ^ other_arg_list)
|
|
if len(res) == 0:
|
|
return Feedback(self, other.args[0])
|
|
elif len(res) == 1:
|
|
return Feedback(self, *res)
|
|
else:
|
|
return Feedback(self, Series(*res))
|
|
else:
|
|
raise ValueError("This transfer function expression is invalid.")
|
|
|
|
def __neg__(self):
|
|
return Series(TransferFunction(-1, 1, self.var), self)
|
|
|
|
def to_expr(self):
|
|
"""Returns the equivalent ``Expr`` object."""
|
|
return Mul(*(arg.to_expr() for arg in self.args), evaluate=False)
|
|
|
|
@property
|
|
def is_proper(self):
|
|
"""
|
|
Returns True if degree of the numerator polynomial of the resultant transfer
|
|
function is less than or equal to degree of the denominator polynomial of
|
|
the same, else False.
|
|
|
|
Examples
|
|
========
|
|
|
|
>>> from sympy.abc import s, p, a, b
|
|
>>> from sympy.physics.control.lti import TransferFunction, Series
|
|
>>> tf1 = TransferFunction(b*s**2 + p**2 - a*p + s, b - p**2, s)
|
|
>>> tf2 = TransferFunction(p**2 - 4*p, p**3 + 3*s + 2, s)
|
|
>>> tf3 = TransferFunction(s, s**2 + s + 1, s)
|
|
>>> S1 = Series(-tf2, tf1)
|
|
>>> S1.is_proper
|
|
False
|
|
>>> S2 = Series(tf1, tf2, tf3)
|
|
>>> S2.is_proper
|
|
True
|
|
|
|
"""
|
|
return self.doit().is_proper
|
|
|
|
@property
|
|
def is_strictly_proper(self):
|
|
"""
|
|
Returns True if degree of the numerator polynomial of the resultant transfer
|
|
function is strictly less than degree of the denominator polynomial of
|
|
the same, else False.
|
|
|
|
Examples
|
|
========
|
|
|
|
>>> from sympy.abc import s, p, a, b
|
|
>>> from sympy.physics.control.lti import TransferFunction, Series
|
|
>>> tf1 = TransferFunction(a*p**2 + b*s, s - p, s)
|
|
>>> tf2 = TransferFunction(s**3 - 2, s**2 + 5*s + 6, s)
|
|
>>> tf3 = TransferFunction(1, s**2 + s + 1, s)
|
|
>>> S1 = Series(tf1, tf2)
|
|
>>> S1.is_strictly_proper
|
|
False
|
|
>>> S2 = Series(tf1, tf2, tf3)
|
|
>>> S2.is_strictly_proper
|
|
True
|
|
|
|
"""
|
|
return self.doit().is_strictly_proper
|
|
|
|
@property
|
|
def is_biproper(self):
|
|
r"""
|
|
Returns True if degree of the numerator polynomial of the resultant transfer
|
|
function is equal to degree of the denominator polynomial of
|
|
the same, else False.
|
|
|
|
Examples
|
|
========
|
|
|
|
>>> from sympy.abc import s, p, a, b
|
|
>>> from sympy.physics.control.lti import TransferFunction, Series
|
|
>>> tf1 = TransferFunction(a*p**2 + b*s, s - p, s)
|
|
>>> tf2 = TransferFunction(p, s**2, s)
|
|
>>> tf3 = TransferFunction(s**2, 1, s)
|
|
>>> S1 = Series(tf1, -tf2)
|
|
>>> S1.is_biproper
|
|
False
|
|
>>> S2 = Series(tf2, tf3)
|
|
>>> S2.is_biproper
|
|
True
|
|
|
|
"""
|
|
return self.doit().is_biproper
|
|
|
|
|
|
def _mat_mul_compatible(*args):
|
|
"""To check whether shapes are compatible for matrix mul."""
|
|
return all(args[i].num_outputs == args[i+1].num_inputs for i in range(len(args)-1))
|
|
|
|
|
|
class MIMOSeries(MIMOLinearTimeInvariant):
|
|
r"""
|
|
A class for representing a series configuration of MIMO systems.
|
|
|
|
Parameters
|
|
==========
|
|
|
|
args : MIMOLinearTimeInvariant
|
|
MIMO systems in a series configuration.
|
|
evaluate : Boolean, Keyword
|
|
When passed ``True``, returns the equivalent
|
|
``MIMOSeries(*args).doit()``. Set to ``False`` by default.
|
|
|
|
Raises
|
|
======
|
|
|
|
ValueError
|
|
When no argument is passed.
|
|
|
|
``var`` attribute is not same for every system.
|
|
|
|
``num_outputs`` of the MIMO system is not equal to the
|
|
``num_inputs`` of its adjacent MIMO system. (Matrix
|
|
multiplication constraint, basically)
|
|
TypeError
|
|
Any of the passed ``*args`` has unsupported type
|
|
|
|
A combination of SISO and MIMO systems is
|
|
passed. There should be homogeneity in the
|
|
type of systems passed, MIMO in this case.
|
|
|
|
Examples
|
|
========
|
|
|
|
>>> from sympy.abc import s
|
|
>>> from sympy.physics.control.lti import MIMOSeries, TransferFunctionMatrix
|
|
>>> from sympy import Matrix, pprint
|
|
>>> mat_a = Matrix([[5*s], [5]]) # 2 Outputs 1 Input
|
|
>>> mat_b = Matrix([[5, 1/(6*s**2)]]) # 1 Output 2 Inputs
|
|
>>> mat_c = Matrix([[1, s], [5/s, 1]]) # 2 Outputs 2 Inputs
|
|
>>> tfm_a = TransferFunctionMatrix.from_Matrix(mat_a, s)
|
|
>>> tfm_b = TransferFunctionMatrix.from_Matrix(mat_b, s)
|
|
>>> tfm_c = TransferFunctionMatrix.from_Matrix(mat_c, s)
|
|
>>> MIMOSeries(tfm_c, tfm_b, tfm_a)
|
|
MIMOSeries(TransferFunctionMatrix(((TransferFunction(1, 1, s), TransferFunction(s, 1, s)), (TransferFunction(5, s, s), TransferFunction(1, 1, s)))), TransferFunctionMatrix(((TransferFunction(5, 1, s), TransferFunction(1, 6*s**2, s)),)), TransferFunctionMatrix(((TransferFunction(5*s, 1, s),), (TransferFunction(5, 1, s),))))
|
|
>>> pprint(_, use_unicode=False) # For Better Visualization
|
|
[5*s] [1 s]
|
|
[---] [5 1 ] [- -]
|
|
[ 1 ] [- ----] [1 1]
|
|
[ ] *[1 2] *[ ]
|
|
[ 5 ] [ 6*s ]{t} [5 1]
|
|
[ - ] [- -]
|
|
[ 1 ]{t} [s 1]{t}
|
|
>>> MIMOSeries(tfm_c, tfm_b, tfm_a).doit()
|
|
TransferFunctionMatrix(((TransferFunction(150*s**4 + 25*s, 6*s**3, s), TransferFunction(150*s**4 + 5*s, 6*s**2, s)), (TransferFunction(150*s**3 + 25, 6*s**3, s), TransferFunction(150*s**3 + 5, 6*s**2, s))))
|
|
>>> pprint(_, use_unicode=False) # (2 Inputs -A-> 2 Outputs) -> (2 Inputs -B-> 1 Output) -> (1 Input -C-> 2 Outputs) is equivalent to (2 Inputs -Series Equivalent-> 2 Outputs).
|
|
[ 4 4 ]
|
|
[150*s + 25*s 150*s + 5*s]
|
|
[------------- ------------]
|
|
[ 3 2 ]
|
|
[ 6*s 6*s ]
|
|
[ ]
|
|
[ 3 3 ]
|
|
[ 150*s + 25 150*s + 5 ]
|
|
[ ----------- ---------- ]
|
|
[ 3 2 ]
|
|
[ 6*s 6*s ]{t}
|
|
|
|
Notes
|
|
=====
|
|
|
|
All the transfer function matrices should use the same complex variable ``var`` of the Laplace transform.
|
|
|
|
``MIMOSeries(A, B)`` is not equivalent to ``A*B``. It is always in the reverse order, that is ``B*A``.
|
|
|
|
See Also
|
|
========
|
|
|
|
Series, MIMOParallel
|
|
|
|
"""
|
|
def __new__(cls, *args, evaluate=False):
|
|
|
|
cls._check_args(args)
|
|
|
|
if _mat_mul_compatible(*args):
|
|
obj = super().__new__(cls, *args)
|
|
|
|
else:
|
|
raise ValueError("Number of input signals do not match the number"
|
|
" of output signals of adjacent systems for some args.")
|
|
|
|
return obj.doit() if evaluate else obj
|
|
|
|
@property
|
|
def var(self):
|
|
"""
|
|
Returns the complex variable used by all the transfer functions.
|
|
|
|
Examples
|
|
========
|
|
|
|
>>> from sympy.abc import p
|
|
>>> from sympy.physics.control.lti import TransferFunction, MIMOSeries, TransferFunctionMatrix
|
|
>>> G1 = TransferFunction(p**2 + 2*p + 4, p - 6, p)
|
|
>>> G2 = TransferFunction(p, 4 - p, p)
|
|
>>> G3 = TransferFunction(0, p**4 - 1, p)
|
|
>>> tfm_1 = TransferFunctionMatrix([[G1, G2, G3]])
|
|
>>> tfm_2 = TransferFunctionMatrix([[G1], [G2], [G3]])
|
|
>>> MIMOSeries(tfm_2, tfm_1).var
|
|
p
|
|
|
|
"""
|
|
return self.args[0].var
|
|
|
|
@property
|
|
def num_inputs(self):
|
|
"""Returns the number of input signals of the series system."""
|
|
return self.args[0].num_inputs
|
|
|
|
@property
|
|
def num_outputs(self):
|
|
"""Returns the number of output signals of the series system."""
|
|
return self.args[-1].num_outputs
|
|
|
|
@property
|
|
def shape(self):
|
|
"""Returns the shape of the equivalent MIMO system."""
|
|
return self.num_outputs, self.num_inputs
|
|
|
|
def doit(self, cancel=False, **kwargs):
|
|
"""
|
|
Returns the resultant transfer function matrix obtained after evaluating
|
|
the MIMO systems arranged in a series configuration.
|
|
|
|
Examples
|
|
========
|
|
|
|
>>> from sympy.abc import s, p, a, b
|
|
>>> from sympy.physics.control.lti import TransferFunction, MIMOSeries, TransferFunctionMatrix
|
|
>>> tf1 = TransferFunction(a*p**2 + b*s, s - p, s)
|
|
>>> tf2 = TransferFunction(s**3 - 2, s**4 + 5*s + 6, s)
|
|
>>> tfm1 = TransferFunctionMatrix([[tf1, tf2], [tf2, tf2]])
|
|
>>> tfm2 = TransferFunctionMatrix([[tf2, tf1], [tf1, tf1]])
|
|
>>> MIMOSeries(tfm2, tfm1).doit()
|
|
TransferFunctionMatrix(((TransferFunction(2*(-p + s)*(s**3 - 2)*(a*p**2 + b*s)*(s**4 + 5*s + 6), (-p + s)**2*(s**4 + 5*s + 6)**2, s), TransferFunction((-p + s)**2*(s**3 - 2)*(a*p**2 + b*s) + (-p + s)*(a*p**2 + b*s)**2*(s**4 + 5*s + 6), (-p + s)**3*(s**4 + 5*s + 6), s)), (TransferFunction((-p + s)*(s**3 - 2)**2*(s**4 + 5*s + 6) + (s**3 - 2)*(a*p**2 + b*s)*(s**4 + 5*s + 6)**2, (-p + s)*(s**4 + 5*s + 6)**3, s), TransferFunction(2*(s**3 - 2)*(a*p**2 + b*s), (-p + s)*(s**4 + 5*s + 6), s))))
|
|
|
|
"""
|
|
_arg = (arg.doit()._expr_mat for arg in reversed(self.args))
|
|
|
|
if cancel:
|
|
res = MatMul(*_arg, evaluate=True)
|
|
return TransferFunctionMatrix.from_Matrix(res, self.var)
|
|
|
|
_dummy_args, _dummy_dict = _dummify_args(_arg, self.var)
|
|
res = MatMul(*_dummy_args, evaluate=True)
|
|
temp_tfm = TransferFunctionMatrix.from_Matrix(res, self.var)
|
|
return temp_tfm.subs(_dummy_dict)
|
|
|
|
def _eval_rewrite_as_TransferFunctionMatrix(self, *args, **kwargs):
|
|
return self.doit()
|
|
|
|
@_check_other_MIMO
|
|
def __add__(self, other):
|
|
|
|
if isinstance(other, MIMOParallel):
|
|
arg_list = list(other.args)
|
|
return MIMOParallel(self, *arg_list)
|
|
|
|
return MIMOParallel(self, other)
|
|
|
|
__radd__ = __add__
|
|
|
|
@_check_other_MIMO
|
|
def __sub__(self, other):
|
|
return self + (-other)
|
|
|
|
def __rsub__(self, other):
|
|
return -self + other
|
|
|
|
@_check_other_MIMO
|
|
def __mul__(self, other):
|
|
|
|
if isinstance(other, MIMOSeries):
|
|
self_arg_list = list(self.args)
|
|
other_arg_list = list(other.args)
|
|
return MIMOSeries(*other_arg_list, *self_arg_list) # A*B = MIMOSeries(B, A)
|
|
|
|
arg_list = list(self.args)
|
|
return MIMOSeries(other, *arg_list)
|
|
|
|
def __neg__(self):
|
|
arg_list = list(self.args)
|
|
arg_list[0] = -arg_list[0]
|
|
return MIMOSeries(*arg_list)
|
|
|
|
|
|
class Parallel(SISOLinearTimeInvariant):
|
|
r"""
|
|
A class for representing a parallel configuration of SISO systems.
|
|
|
|
Parameters
|
|
==========
|
|
|
|
args : SISOLinearTimeInvariant
|
|
SISO systems in a parallel arrangement.
|
|
evaluate : Boolean, Keyword
|
|
When passed ``True``, returns the equivalent
|
|
``Parallel(*args).doit()``. Set to ``False`` by default.
|
|
|
|
Raises
|
|
======
|
|
|
|
ValueError
|
|
When no argument is passed.
|
|
|
|
``var`` attribute is not same for every system.
|
|
TypeError
|
|
Any of the passed ``*args`` has unsupported type
|
|
|
|
A combination of SISO and MIMO systems is
|
|
passed. There should be homogeneity in the
|
|
type of systems passed.
|
|
|
|
Examples
|
|
========
|
|
|
|
>>> from sympy.abc import s, p, a, b
|
|
>>> from sympy.physics.control.lti import TransferFunction, Parallel, Series
|
|
>>> tf1 = TransferFunction(a*p**2 + b*s, s - p, s)
|
|
>>> tf2 = TransferFunction(s**3 - 2, s**4 + 5*s + 6, s)
|
|
>>> tf3 = TransferFunction(p**2, p + s, s)
|
|
>>> P1 = Parallel(tf1, tf2)
|
|
>>> P1
|
|
Parallel(TransferFunction(a*p**2 + b*s, -p + s, s), TransferFunction(s**3 - 2, s**4 + 5*s + 6, s))
|
|
>>> P1.var
|
|
s
|
|
>>> P2 = Parallel(tf2, Series(tf3, -tf1))
|
|
>>> P2
|
|
Parallel(TransferFunction(s**3 - 2, s**4 + 5*s + 6, s), Series(TransferFunction(p**2, p + s, s), TransferFunction(-a*p**2 - b*s, -p + s, s)))
|
|
>>> P2.var
|
|
s
|
|
>>> P3 = Parallel(Series(tf1, tf2), Series(tf2, tf3))
|
|
>>> P3
|
|
Parallel(Series(TransferFunction(a*p**2 + b*s, -p + s, s), TransferFunction(s**3 - 2, s**4 + 5*s + 6, s)), Series(TransferFunction(s**3 - 2, s**4 + 5*s + 6, s), TransferFunction(p**2, p + s, s)))
|
|
>>> P3.var
|
|
s
|
|
|
|
You can get the resultant transfer function by using ``.doit()`` method:
|
|
|
|
>>> Parallel(tf1, tf2, -tf3).doit()
|
|
TransferFunction(-p**2*(-p + s)*(s**4 + 5*s + 6) + (-p + s)*(p + s)*(s**3 - 2) + (p + s)*(a*p**2 + b*s)*(s**4 + 5*s + 6), (-p + s)*(p + s)*(s**4 + 5*s + 6), s)
|
|
>>> Parallel(tf2, Series(tf1, -tf3)).doit()
|
|
TransferFunction(-p**2*(a*p**2 + b*s)*(s**4 + 5*s + 6) + (-p + s)*(p + s)*(s**3 - 2), (-p + s)*(p + s)*(s**4 + 5*s + 6), s)
|
|
|
|
Notes
|
|
=====
|
|
|
|
All the transfer functions should use the same complex variable
|
|
``var`` of the Laplace transform.
|
|
|
|
See Also
|
|
========
|
|
|
|
Series, TransferFunction, Feedback
|
|
|
|
"""
|
|
def __new__(cls, *args, evaluate=False):
|
|
|
|
args = _flatten_args(args, Parallel)
|
|
cls._check_args(args)
|
|
obj = super().__new__(cls, *args)
|
|
|
|
return obj.doit() if evaluate else obj
|
|
|
|
@property
|
|
def var(self):
|
|
"""
|
|
Returns the complex variable used by all the transfer functions.
|
|
|
|
Examples
|
|
========
|
|
|
|
>>> from sympy.abc import p
|
|
>>> from sympy.physics.control.lti import TransferFunction, Parallel, Series
|
|
>>> G1 = TransferFunction(p**2 + 2*p + 4, p - 6, p)
|
|
>>> G2 = TransferFunction(p, 4 - p, p)
|
|
>>> G3 = TransferFunction(0, p**4 - 1, p)
|
|
>>> Parallel(G1, G2).var
|
|
p
|
|
>>> Parallel(-G3, Series(G1, G2)).var
|
|
p
|
|
|
|
"""
|
|
return self.args[0].var
|
|
|
|
def doit(self, **kwargs):
|
|
"""
|
|
Returns the resultant transfer function obtained after evaluating
|
|
the transfer functions in parallel configuration.
|
|
|
|
Examples
|
|
========
|
|
|
|
>>> from sympy.abc import s, p, a, b
|
|
>>> from sympy.physics.control.lti import TransferFunction, Parallel
|
|
>>> tf1 = TransferFunction(a*p**2 + b*s, s - p, s)
|
|
>>> tf2 = TransferFunction(s**3 - 2, s**4 + 5*s + 6, s)
|
|
>>> Parallel(tf2, tf1).doit()
|
|
TransferFunction((-p + s)*(s**3 - 2) + (a*p**2 + b*s)*(s**4 + 5*s + 6), (-p + s)*(s**4 + 5*s + 6), s)
|
|
>>> Parallel(-tf1, -tf2).doit()
|
|
TransferFunction((2 - s**3)*(-p + s) + (-a*p**2 - b*s)*(s**4 + 5*s + 6), (-p + s)*(s**4 + 5*s + 6), s)
|
|
|
|
"""
|
|
|
|
_arg = (arg.doit().to_expr() for arg in self.args)
|
|
res = Add(*_arg).as_numer_denom()
|
|
return TransferFunction(*res, self.var)
|
|
|
|
def _eval_rewrite_as_TransferFunction(self, *args, **kwargs):
|
|
return self.doit()
|
|
|
|
@_check_other_SISO
|
|
def __add__(self, other):
|
|
|
|
self_arg_list = list(self.args)
|
|
return Parallel(*self_arg_list, other)
|
|
|
|
__radd__ = __add__
|
|
|
|
@_check_other_SISO
|
|
def __sub__(self, other):
|
|
return self + (-other)
|
|
|
|
def __rsub__(self, other):
|
|
return -self + other
|
|
|
|
@_check_other_SISO
|
|
def __mul__(self, other):
|
|
|
|
if isinstance(other, Series):
|
|
arg_list = list(other.args)
|
|
return Series(self, *arg_list)
|
|
|
|
return Series(self, other)
|
|
|
|
def __neg__(self):
|
|
return Series(TransferFunction(-1, 1, self.var), self)
|
|
|
|
def to_expr(self):
|
|
"""Returns the equivalent ``Expr`` object."""
|
|
return Add(*(arg.to_expr() for arg in self.args), evaluate=False)
|
|
|
|
@property
|
|
def is_proper(self):
|
|
"""
|
|
Returns True if degree of the numerator polynomial of the resultant transfer
|
|
function is less than or equal to degree of the denominator polynomial of
|
|
the same, else False.
|
|
|
|
Examples
|
|
========
|
|
|
|
>>> from sympy.abc import s, p, a, b
|
|
>>> from sympy.physics.control.lti import TransferFunction, Parallel
|
|
>>> tf1 = TransferFunction(b*s**2 + p**2 - a*p + s, b - p**2, s)
|
|
>>> tf2 = TransferFunction(p**2 - 4*p, p**3 + 3*s + 2, s)
|
|
>>> tf3 = TransferFunction(s, s**2 + s + 1, s)
|
|
>>> P1 = Parallel(-tf2, tf1)
|
|
>>> P1.is_proper
|
|
False
|
|
>>> P2 = Parallel(tf2, tf3)
|
|
>>> P2.is_proper
|
|
True
|
|
|
|
"""
|
|
return self.doit().is_proper
|
|
|
|
@property
|
|
def is_strictly_proper(self):
|
|
"""
|
|
Returns True if degree of the numerator polynomial of the resultant transfer
|
|
function is strictly less than degree of the denominator polynomial of
|
|
the same, else False.
|
|
|
|
Examples
|
|
========
|
|
|
|
>>> from sympy.abc import s, p, a, b
|
|
>>> from sympy.physics.control.lti import TransferFunction, Parallel
|
|
>>> tf1 = TransferFunction(a*p**2 + b*s, s - p, s)
|
|
>>> tf2 = TransferFunction(s**3 - 2, s**4 + 5*s + 6, s)
|
|
>>> tf3 = TransferFunction(s, s**2 + s + 1, s)
|
|
>>> P1 = Parallel(tf1, tf2)
|
|
>>> P1.is_strictly_proper
|
|
False
|
|
>>> P2 = Parallel(tf2, tf3)
|
|
>>> P2.is_strictly_proper
|
|
True
|
|
|
|
"""
|
|
return self.doit().is_strictly_proper
|
|
|
|
@property
|
|
def is_biproper(self):
|
|
"""
|
|
Returns True if degree of the numerator polynomial of the resultant transfer
|
|
function is equal to degree of the denominator polynomial of
|
|
the same, else False.
|
|
|
|
Examples
|
|
========
|
|
|
|
>>> from sympy.abc import s, p, a, b
|
|
>>> from sympy.physics.control.lti import TransferFunction, Parallel
|
|
>>> tf1 = TransferFunction(a*p**2 + b*s, s - p, s)
|
|
>>> tf2 = TransferFunction(p**2, p + s, s)
|
|
>>> tf3 = TransferFunction(s, s**2 + s + 1, s)
|
|
>>> P1 = Parallel(tf1, -tf2)
|
|
>>> P1.is_biproper
|
|
True
|
|
>>> P2 = Parallel(tf2, tf3)
|
|
>>> P2.is_biproper
|
|
False
|
|
|
|
"""
|
|
return self.doit().is_biproper
|
|
|
|
|
|
class MIMOParallel(MIMOLinearTimeInvariant):
|
|
r"""
|
|
A class for representing a parallel configuration of MIMO systems.
|
|
|
|
Parameters
|
|
==========
|
|
|
|
args : MIMOLinearTimeInvariant
|
|
MIMO Systems in a parallel arrangement.
|
|
evaluate : Boolean, Keyword
|
|
When passed ``True``, returns the equivalent
|
|
``MIMOParallel(*args).doit()``. Set to ``False`` by default.
|
|
|
|
Raises
|
|
======
|
|
|
|
ValueError
|
|
When no argument is passed.
|
|
|
|
``var`` attribute is not same for every system.
|
|
|
|
All MIMO systems passed don't have same shape.
|
|
TypeError
|
|
Any of the passed ``*args`` has unsupported type
|
|
|
|
A combination of SISO and MIMO systems is
|
|
passed. There should be homogeneity in the
|
|
type of systems passed, MIMO in this case.
|
|
|
|
Examples
|
|
========
|
|
|
|
>>> from sympy.abc import s
|
|
>>> from sympy.physics.control.lti import TransferFunctionMatrix, MIMOParallel
|
|
>>> from sympy import Matrix, pprint
|
|
>>> expr_1 = 1/s
|
|
>>> expr_2 = s/(s**2-1)
|
|
>>> expr_3 = (2 + s)/(s**2 - 1)
|
|
>>> expr_4 = 5
|
|
>>> tfm_a = TransferFunctionMatrix.from_Matrix(Matrix([[expr_1, expr_2], [expr_3, expr_4]]), s)
|
|
>>> tfm_b = TransferFunctionMatrix.from_Matrix(Matrix([[expr_2, expr_1], [expr_4, expr_3]]), s)
|
|
>>> tfm_c = TransferFunctionMatrix.from_Matrix(Matrix([[expr_3, expr_4], [expr_1, expr_2]]), s)
|
|
>>> MIMOParallel(tfm_a, tfm_b, tfm_c)
|
|
MIMOParallel(TransferFunctionMatrix(((TransferFunction(1, s, s), TransferFunction(s, s**2 - 1, s)), (TransferFunction(s + 2, s**2 - 1, s), TransferFunction(5, 1, s)))), TransferFunctionMatrix(((TransferFunction(s, s**2 - 1, s), TransferFunction(1, s, s)), (TransferFunction(5, 1, s), TransferFunction(s + 2, s**2 - 1, s)))), TransferFunctionMatrix(((TransferFunction(s + 2, s**2 - 1, s), TransferFunction(5, 1, s)), (TransferFunction(1, s, s), TransferFunction(s, s**2 - 1, s)))))
|
|
>>> pprint(_, use_unicode=False) # For Better Visualization
|
|
[ 1 s ] [ s 1 ] [s + 2 5 ]
|
|
[ - ------] [------ - ] [------ - ]
|
|
[ s 2 ] [ 2 s ] [ 2 1 ]
|
|
[ s - 1] [s - 1 ] [s - 1 ]
|
|
[ ] + [ ] + [ ]
|
|
[s + 2 5 ] [ 5 s + 2 ] [ 1 s ]
|
|
[------ - ] [ - ------] [ - ------]
|
|
[ 2 1 ] [ 1 2 ] [ s 2 ]
|
|
[s - 1 ]{t} [ s - 1]{t} [ s - 1]{t}
|
|
>>> MIMOParallel(tfm_a, tfm_b, tfm_c).doit()
|
|
TransferFunctionMatrix(((TransferFunction(s**2 + s*(2*s + 2) - 1, s*(s**2 - 1), s), TransferFunction(2*s**2 + 5*s*(s**2 - 1) - 1, s*(s**2 - 1), s)), (TransferFunction(s**2 + s*(s + 2) + 5*s*(s**2 - 1) - 1, s*(s**2 - 1), s), TransferFunction(5*s**2 + 2*s - 3, s**2 - 1, s))))
|
|
>>> pprint(_, use_unicode=False)
|
|
[ 2 2 / 2 \ ]
|
|
[ s + s*(2*s + 2) - 1 2*s + 5*s*\s - 1/ - 1]
|
|
[ -------------------- -----------------------]
|
|
[ / 2 \ / 2 \ ]
|
|
[ s*\s - 1/ s*\s - 1/ ]
|
|
[ ]
|
|
[ 2 / 2 \ 2 ]
|
|
[s + s*(s + 2) + 5*s*\s - 1/ - 1 5*s + 2*s - 3 ]
|
|
[--------------------------------- -------------- ]
|
|
[ / 2 \ 2 ]
|
|
[ s*\s - 1/ s - 1 ]{t}
|
|
|
|
Notes
|
|
=====
|
|
|
|
All the transfer function matrices should use the same complex variable
|
|
``var`` of the Laplace transform.
|
|
|
|
See Also
|
|
========
|
|
|
|
Parallel, MIMOSeries
|
|
|
|
"""
|
|
def __new__(cls, *args, evaluate=False):
|
|
|
|
args = _flatten_args(args, MIMOParallel)
|
|
|
|
cls._check_args(args)
|
|
|
|
if any(arg.shape != args[0].shape for arg in args):
|
|
raise TypeError("Shape of all the args is not equal.")
|
|
|
|
obj = super().__new__(cls, *args)
|
|
|
|
return obj.doit() if evaluate else obj
|
|
|
|
@property
|
|
def var(self):
|
|
"""
|
|
Returns the complex variable used by all the systems.
|
|
|
|
Examples
|
|
========
|
|
|
|
>>> from sympy.abc import p
|
|
>>> from sympy.physics.control.lti import TransferFunction, TransferFunctionMatrix, MIMOParallel
|
|
>>> G1 = TransferFunction(p**2 + 2*p + 4, p - 6, p)
|
|
>>> G2 = TransferFunction(p, 4 - p, p)
|
|
>>> G3 = TransferFunction(0, p**4 - 1, p)
|
|
>>> G4 = TransferFunction(p**2, p**2 - 1, p)
|
|
>>> tfm_a = TransferFunctionMatrix([[G1, G2], [G3, G4]])
|
|
>>> tfm_b = TransferFunctionMatrix([[G2, G1], [G4, G3]])
|
|
>>> MIMOParallel(tfm_a, tfm_b).var
|
|
p
|
|
|
|
"""
|
|
return self.args[0].var
|
|
|
|
@property
|
|
def num_inputs(self):
|
|
"""Returns the number of input signals of the parallel system."""
|
|
return self.args[0].num_inputs
|
|
|
|
@property
|
|
def num_outputs(self):
|
|
"""Returns the number of output signals of the parallel system."""
|
|
return self.args[0].num_outputs
|
|
|
|
@property
|
|
def shape(self):
|
|
"""Returns the shape of the equivalent MIMO system."""
|
|
return self.num_outputs, self.num_inputs
|
|
|
|
def doit(self, **kwargs):
|
|
"""
|
|
Returns the resultant transfer function matrix obtained after evaluating
|
|
the MIMO systems arranged in a parallel configuration.
|
|
|
|
Examples
|
|
========
|
|
|
|
>>> from sympy.abc import s, p, a, b
|
|
>>> from sympy.physics.control.lti import TransferFunction, MIMOParallel, TransferFunctionMatrix
|
|
>>> tf1 = TransferFunction(a*p**2 + b*s, s - p, s)
|
|
>>> tf2 = TransferFunction(s**3 - 2, s**4 + 5*s + 6, s)
|
|
>>> tfm_1 = TransferFunctionMatrix([[tf1, tf2], [tf2, tf1]])
|
|
>>> tfm_2 = TransferFunctionMatrix([[tf2, tf1], [tf1, tf2]])
|
|
>>> MIMOParallel(tfm_1, tfm_2).doit()
|
|
TransferFunctionMatrix(((TransferFunction((-p + s)*(s**3 - 2) + (a*p**2 + b*s)*(s**4 + 5*s + 6), (-p + s)*(s**4 + 5*s + 6), s), TransferFunction((-p + s)*(s**3 - 2) + (a*p**2 + b*s)*(s**4 + 5*s + 6), (-p + s)*(s**4 + 5*s + 6), s)), (TransferFunction((-p + s)*(s**3 - 2) + (a*p**2 + b*s)*(s**4 + 5*s + 6), (-p + s)*(s**4 + 5*s + 6), s), TransferFunction((-p + s)*(s**3 - 2) + (a*p**2 + b*s)*(s**4 + 5*s + 6), (-p + s)*(s**4 + 5*s + 6), s))))
|
|
|
|
"""
|
|
_arg = (arg.doit()._expr_mat for arg in self.args)
|
|
res = MatAdd(*_arg, evaluate=True)
|
|
return TransferFunctionMatrix.from_Matrix(res, self.var)
|
|
|
|
def _eval_rewrite_as_TransferFunctionMatrix(self, *args, **kwargs):
|
|
return self.doit()
|
|
|
|
@_check_other_MIMO
|
|
def __add__(self, other):
|
|
|
|
self_arg_list = list(self.args)
|
|
return MIMOParallel(*self_arg_list, other)
|
|
|
|
__radd__ = __add__
|
|
|
|
@_check_other_MIMO
|
|
def __sub__(self, other):
|
|
return self + (-other)
|
|
|
|
def __rsub__(self, other):
|
|
return -self + other
|
|
|
|
@_check_other_MIMO
|
|
def __mul__(self, other):
|
|
|
|
if isinstance(other, MIMOSeries):
|
|
arg_list = list(other.args)
|
|
return MIMOSeries(*arg_list, self)
|
|
|
|
return MIMOSeries(other, self)
|
|
|
|
def __neg__(self):
|
|
arg_list = [-arg for arg in list(self.args)]
|
|
return MIMOParallel(*arg_list)
|
|
|
|
|
|
class Feedback(SISOLinearTimeInvariant):
|
|
r"""
|
|
A class for representing closed-loop feedback interconnection between two
|
|
SISO input/output systems.
|
|
|
|
The first argument, ``sys1``, is the feedforward part of the closed-loop
|
|
system or in simple words, the dynamical model representing the process
|
|
to be controlled. The second argument, ``sys2``, is the feedback system
|
|
and controls the fed back signal to ``sys1``. Both ``sys1`` and ``sys2``
|
|
can either be ``Series`` or ``TransferFunction`` objects.
|
|
|
|
Parameters
|
|
==========
|
|
|
|
sys1 : Series, TransferFunction
|
|
The feedforward path system.
|
|
sys2 : Series, TransferFunction, optional
|
|
The feedback path system (often a feedback controller).
|
|
It is the model sitting on the feedback path.
|
|
|
|
If not specified explicitly, the sys2 is
|
|
assumed to be unit (1.0) transfer function.
|
|
sign : int, optional
|
|
The sign of feedback. Can either be ``1``
|
|
(for positive feedback) or ``-1`` (for negative feedback).
|
|
Default value is `-1`.
|
|
|
|
Raises
|
|
======
|
|
|
|
ValueError
|
|
When ``sys1`` and ``sys2`` are not using the
|
|
same complex variable of the Laplace transform.
|
|
|
|
When a combination of ``sys1`` and ``sys2`` yields
|
|
zero denominator.
|
|
|
|
TypeError
|
|
When either ``sys1`` or ``sys2`` is not a ``Series`` or a
|
|
``TransferFunction`` object.
|
|
|
|
Examples
|
|
========
|
|
|
|
>>> from sympy.abc import s
|
|
>>> from sympy.physics.control.lti import TransferFunction, Feedback
|
|
>>> plant = TransferFunction(3*s**2 + 7*s - 3, s**2 - 4*s + 2, s)
|
|
>>> controller = TransferFunction(5*s - 10, s + 7, s)
|
|
>>> F1 = Feedback(plant, controller)
|
|
>>> F1
|
|
Feedback(TransferFunction(3*s**2 + 7*s - 3, s**2 - 4*s + 2, s), TransferFunction(5*s - 10, s + 7, s), -1)
|
|
>>> F1.var
|
|
s
|
|
>>> F1.args
|
|
(TransferFunction(3*s**2 + 7*s - 3, s**2 - 4*s + 2, s), TransferFunction(5*s - 10, s + 7, s), -1)
|
|
|
|
You can get the feedforward and feedback path systems by using ``.sys1`` and ``.sys2`` respectively.
|
|
|
|
>>> F1.sys1
|
|
TransferFunction(3*s**2 + 7*s - 3, s**2 - 4*s + 2, s)
|
|
>>> F1.sys2
|
|
TransferFunction(5*s - 10, s + 7, s)
|
|
|
|
You can get the resultant closed loop transfer function obtained by negative feedback
|
|
interconnection using ``.doit()`` method.
|
|
|
|
>>> F1.doit()
|
|
TransferFunction((s + 7)*(s**2 - 4*s + 2)*(3*s**2 + 7*s - 3), ((s + 7)*(s**2 - 4*s + 2) + (5*s - 10)*(3*s**2 + 7*s - 3))*(s**2 - 4*s + 2), s)
|
|
>>> G = TransferFunction(2*s**2 + 5*s + 1, s**2 + 2*s + 3, s)
|
|
>>> C = TransferFunction(5*s + 10, s + 10, s)
|
|
>>> F2 = Feedback(G*C, TransferFunction(1, 1, s))
|
|
>>> F2.doit()
|
|
TransferFunction((s + 10)*(5*s + 10)*(s**2 + 2*s + 3)*(2*s**2 + 5*s + 1), (s + 10)*((s + 10)*(s**2 + 2*s + 3) + (5*s + 10)*(2*s**2 + 5*s + 1))*(s**2 + 2*s + 3), s)
|
|
|
|
To negate a ``Feedback`` object, the ``-`` operator can be prepended:
|
|
|
|
>>> -F1
|
|
Feedback(TransferFunction(-3*s**2 - 7*s + 3, s**2 - 4*s + 2, s), TransferFunction(10 - 5*s, s + 7, s), -1)
|
|
>>> -F2
|
|
Feedback(Series(TransferFunction(-1, 1, s), TransferFunction(2*s**2 + 5*s + 1, s**2 + 2*s + 3, s), TransferFunction(5*s + 10, s + 10, s)), TransferFunction(-1, 1, s), -1)
|
|
|
|
See Also
|
|
========
|
|
|
|
MIMOFeedback, Series, Parallel
|
|
|
|
"""
|
|
def __new__(cls, sys1, sys2=None, sign=-1):
|
|
if not sys2:
|
|
sys2 = TransferFunction(1, 1, sys1.var)
|
|
|
|
if not (isinstance(sys1, (TransferFunction, Series))
|
|
and isinstance(sys2, (TransferFunction, Series))):
|
|
raise TypeError("Unsupported type for `sys1` or `sys2` of Feedback.")
|
|
|
|
if sign not in [-1, 1]:
|
|
raise ValueError("Unsupported type for feedback. `sign` arg should "
|
|
"either be 1 (positive feedback loop) or -1 (negative feedback loop).")
|
|
|
|
if Mul(sys1.to_expr(), sys2.to_expr()).simplify() == sign:
|
|
raise ValueError("The equivalent system will have zero denominator.")
|
|
|
|
if sys1.var != sys2.var:
|
|
raise ValueError("Both `sys1` and `sys2` should be using the"
|
|
" same complex variable.")
|
|
|
|
return super().__new__(cls, sys1, sys2, _sympify(sign))
|
|
|
|
@property
|
|
def sys1(self):
|
|
"""
|
|
Returns the feedforward system of the feedback interconnection.
|
|
|
|
Examples
|
|
========
|
|
|
|
>>> from sympy.abc import s, p
|
|
>>> from sympy.physics.control.lti import TransferFunction, Feedback
|
|
>>> plant = TransferFunction(3*s**2 + 7*s - 3, s**2 - 4*s + 2, s)
|
|
>>> controller = TransferFunction(5*s - 10, s + 7, s)
|
|
>>> F1 = Feedback(plant, controller)
|
|
>>> F1.sys1
|
|
TransferFunction(3*s**2 + 7*s - 3, s**2 - 4*s + 2, s)
|
|
>>> G = TransferFunction(2*s**2 + 5*s + 1, p**2 + 2*p + 3, p)
|
|
>>> C = TransferFunction(5*p + 10, p + 10, p)
|
|
>>> P = TransferFunction(1 - s, p + 2, p)
|
|
>>> F2 = Feedback(TransferFunction(1, 1, p), G*C*P)
|
|
>>> F2.sys1
|
|
TransferFunction(1, 1, p)
|
|
|
|
"""
|
|
return self.args[0]
|
|
|
|
@property
|
|
def sys2(self):
|
|
"""
|
|
Returns the feedback controller of the feedback interconnection.
|
|
|
|
Examples
|
|
========
|
|
|
|
>>> from sympy.abc import s, p
|
|
>>> from sympy.physics.control.lti import TransferFunction, Feedback
|
|
>>> plant = TransferFunction(3*s**2 + 7*s - 3, s**2 - 4*s + 2, s)
|
|
>>> controller = TransferFunction(5*s - 10, s + 7, s)
|
|
>>> F1 = Feedback(plant, controller)
|
|
>>> F1.sys2
|
|
TransferFunction(5*s - 10, s + 7, s)
|
|
>>> G = TransferFunction(2*s**2 + 5*s + 1, p**2 + 2*p + 3, p)
|
|
>>> C = TransferFunction(5*p + 10, p + 10, p)
|
|
>>> P = TransferFunction(1 - s, p + 2, p)
|
|
>>> F2 = Feedback(TransferFunction(1, 1, p), G*C*P)
|
|
>>> F2.sys2
|
|
Series(TransferFunction(2*s**2 + 5*s + 1, p**2 + 2*p + 3, p), TransferFunction(5*p + 10, p + 10, p), TransferFunction(1 - s, p + 2, p))
|
|
|
|
"""
|
|
return self.args[1]
|
|
|
|
@property
|
|
def var(self):
|
|
"""
|
|
Returns the complex variable of the Laplace transform used by all
|
|
the transfer functions involved in the feedback interconnection.
|
|
|
|
Examples
|
|
========
|
|
|
|
>>> from sympy.abc import s, p
|
|
>>> from sympy.physics.control.lti import TransferFunction, Feedback
|
|
>>> plant = TransferFunction(3*s**2 + 7*s - 3, s**2 - 4*s + 2, s)
|
|
>>> controller = TransferFunction(5*s - 10, s + 7, s)
|
|
>>> F1 = Feedback(plant, controller)
|
|
>>> F1.var
|
|
s
|
|
>>> G = TransferFunction(2*s**2 + 5*s + 1, p**2 + 2*p + 3, p)
|
|
>>> C = TransferFunction(5*p + 10, p + 10, p)
|
|
>>> P = TransferFunction(1 - s, p + 2, p)
|
|
>>> F2 = Feedback(TransferFunction(1, 1, p), G*C*P)
|
|
>>> F2.var
|
|
p
|
|
|
|
"""
|
|
return self.sys1.var
|
|
|
|
@property
|
|
def sign(self):
|
|
"""
|
|
Returns the type of MIMO Feedback model. ``1``
|
|
for Positive and ``-1`` for Negative.
|
|
"""
|
|
return self.args[2]
|
|
|
|
@property
|
|
def sensitivity(self):
|
|
"""
|
|
Returns the sensitivity function of the feedback loop.
|
|
|
|
Sensitivity of a Feedback system is the ratio
|
|
of change in the open loop gain to the change in
|
|
the closed loop gain.
|
|
|
|
.. note::
|
|
This method would not return the complementary
|
|
sensitivity function.
|
|
|
|
Examples
|
|
========
|
|
|
|
>>> from sympy.abc import p
|
|
>>> from sympy.physics.control.lti import TransferFunction, Feedback
|
|
>>> C = TransferFunction(5*p + 10, p + 10, p)
|
|
>>> P = TransferFunction(1 - p, p + 2, p)
|
|
>>> F_1 = Feedback(P, C)
|
|
>>> F_1.sensitivity
|
|
1/((1 - p)*(5*p + 10)/((p + 2)*(p + 10)) + 1)
|
|
|
|
"""
|
|
|
|
return 1/(1 - self.sign*self.sys1.to_expr()*self.sys2.to_expr())
|
|
|
|
def doit(self, cancel=False, expand=False, **kwargs):
|
|
"""
|
|
Returns the resultant transfer function obtained by the
|
|
feedback interconnection.
|
|
|
|
Examples
|
|
========
|
|
|
|
>>> from sympy.abc import s
|
|
>>> from sympy.physics.control.lti import TransferFunction, Feedback
|
|
>>> plant = TransferFunction(3*s**2 + 7*s - 3, s**2 - 4*s + 2, s)
|
|
>>> controller = TransferFunction(5*s - 10, s + 7, s)
|
|
>>> F1 = Feedback(plant, controller)
|
|
>>> F1.doit()
|
|
TransferFunction((s + 7)*(s**2 - 4*s + 2)*(3*s**2 + 7*s - 3), ((s + 7)*(s**2 - 4*s + 2) + (5*s - 10)*(3*s**2 + 7*s - 3))*(s**2 - 4*s + 2), s)
|
|
>>> G = TransferFunction(2*s**2 + 5*s + 1, s**2 + 2*s + 3, s)
|
|
>>> F2 = Feedback(G, TransferFunction(1, 1, s))
|
|
>>> F2.doit()
|
|
TransferFunction((s**2 + 2*s + 3)*(2*s**2 + 5*s + 1), (s**2 + 2*s + 3)*(3*s**2 + 7*s + 4), s)
|
|
|
|
Use kwarg ``expand=True`` to expand the resultant transfer function.
|
|
Use ``cancel=True`` to cancel out the common terms in numerator and
|
|
denominator.
|
|
|
|
>>> F2.doit(cancel=True, expand=True)
|
|
TransferFunction(2*s**2 + 5*s + 1, 3*s**2 + 7*s + 4, s)
|
|
>>> F2.doit(expand=True)
|
|
TransferFunction(2*s**4 + 9*s**3 + 17*s**2 + 17*s + 3, 3*s**4 + 13*s**3 + 27*s**2 + 29*s + 12, s)
|
|
|
|
"""
|
|
arg_list = list(self.sys1.args) if isinstance(self.sys1, Series) else [self.sys1]
|
|
# F_n and F_d are resultant TFs of num and den of Feedback.
|
|
F_n, unit = self.sys1.doit(), TransferFunction(1, 1, self.sys1.var)
|
|
if self.sign == -1:
|
|
F_d = Parallel(unit, Series(self.sys2, *arg_list)).doit()
|
|
else:
|
|
F_d = Parallel(unit, -Series(self.sys2, *arg_list)).doit()
|
|
|
|
_resultant_tf = TransferFunction(F_n.num * F_d.den, F_n.den * F_d.num, F_n.var)
|
|
|
|
if cancel:
|
|
_resultant_tf = _resultant_tf.simplify()
|
|
|
|
if expand:
|
|
_resultant_tf = _resultant_tf.expand()
|
|
|
|
return _resultant_tf
|
|
|
|
def _eval_rewrite_as_TransferFunction(self, num, den, sign, **kwargs):
|
|
return self.doit()
|
|
|
|
def __neg__(self):
|
|
return Feedback(-self.sys1, -self.sys2, self.sign)
|
|
|
|
|
|
def _is_invertible(a, b, sign):
|
|
"""
|
|
Checks whether a given pair of MIMO
|
|
systems passed is invertible or not.
|
|
"""
|
|
_mat = eye(a.num_outputs) - sign*(a.doit()._expr_mat)*(b.doit()._expr_mat)
|
|
_det = _mat.det()
|
|
|
|
return _det != 0
|
|
|
|
|
|
class MIMOFeedback(MIMOLinearTimeInvariant):
|
|
r"""
|
|
A class for representing closed-loop feedback interconnection between two
|
|
MIMO input/output systems.
|
|
|
|
Parameters
|
|
==========
|
|
|
|
sys1 : MIMOSeries, TransferFunctionMatrix
|
|
The MIMO system placed on the feedforward path.
|
|
sys2 : MIMOSeries, TransferFunctionMatrix
|
|
The system placed on the feedback path
|
|
(often a feedback controller).
|
|
sign : int, optional
|
|
The sign of feedback. Can either be ``1``
|
|
(for positive feedback) or ``-1`` (for negative feedback).
|
|
Default value is `-1`.
|
|
|
|
Raises
|
|
======
|
|
|
|
ValueError
|
|
When ``sys1`` and ``sys2`` are not using the
|
|
same complex variable of the Laplace transform.
|
|
|
|
Forward path model should have an equal number of inputs/outputs
|
|
to the feedback path outputs/inputs.
|
|
|
|
When product of ``sys1`` and ``sys2`` is not a square matrix.
|
|
|
|
When the equivalent MIMO system is not invertible.
|
|
|
|
TypeError
|
|
When either ``sys1`` or ``sys2`` is not a ``MIMOSeries`` or a
|
|
``TransferFunctionMatrix`` object.
|
|
|
|
Examples
|
|
========
|
|
|
|
>>> from sympy import Matrix, pprint
|
|
>>> from sympy.abc import s
|
|
>>> from sympy.physics.control.lti import TransferFunctionMatrix, MIMOFeedback
|
|
>>> plant_mat = Matrix([[1, 1/s], [0, 1]])
|
|
>>> controller_mat = Matrix([[10, 0], [0, 10]]) # Constant Gain
|
|
>>> plant = TransferFunctionMatrix.from_Matrix(plant_mat, s)
|
|
>>> controller = TransferFunctionMatrix.from_Matrix(controller_mat, s)
|
|
>>> feedback = MIMOFeedback(plant, controller) # Negative Feedback (default)
|
|
>>> pprint(feedback, use_unicode=False)
|
|
/ [1 1] [10 0 ] \-1 [1 1]
|
|
| [- -] [-- - ] | [- -]
|
|
| [1 s] [1 1 ] | [1 s]
|
|
|I + [ ] *[ ] | * [ ]
|
|
| [0 1] [0 10] | [0 1]
|
|
| [- -] [- --] | [- -]
|
|
\ [1 1]{t} [1 1 ]{t}/ [1 1]{t}
|
|
|
|
To get the equivalent system matrix, use either ``doit`` or ``rewrite`` method.
|
|
|
|
>>> pprint(feedback.doit(), use_unicode=False)
|
|
[1 1 ]
|
|
[-- -----]
|
|
[11 121*s]
|
|
[ ]
|
|
[0 1 ]
|
|
[- -- ]
|
|
[1 11 ]{t}
|
|
|
|
To negate the ``MIMOFeedback`` object, use ``-`` operator.
|
|
|
|
>>> neg_feedback = -feedback
|
|
>>> pprint(neg_feedback.doit(), use_unicode=False)
|
|
[-1 -1 ]
|
|
[--- -----]
|
|
[ 11 121*s]
|
|
[ ]
|
|
[ 0 -1 ]
|
|
[ - --- ]
|
|
[ 1 11 ]{t}
|
|
|
|
See Also
|
|
========
|
|
|
|
Feedback, MIMOSeries, MIMOParallel
|
|
|
|
"""
|
|
def __new__(cls, sys1, sys2, sign=-1):
|
|
if not (isinstance(sys1, (TransferFunctionMatrix, MIMOSeries))
|
|
and isinstance(sys2, (TransferFunctionMatrix, MIMOSeries))):
|
|
raise TypeError("Unsupported type for `sys1` or `sys2` of MIMO Feedback.")
|
|
|
|
if sys1.num_inputs != sys2.num_outputs or \
|
|
sys1.num_outputs != sys2.num_inputs:
|
|
raise ValueError("Product of `sys1` and `sys2` "
|
|
"must yield a square matrix.")
|
|
|
|
if sign not in [-1, 1]:
|
|
raise ValueError("Unsupported type for feedback. `sign` arg should "
|
|
"either be 1 (positive feedback loop) or -1 (negative feedback loop).")
|
|
|
|
if not _is_invertible(sys1, sys2, sign):
|
|
raise ValueError("Non-Invertible system inputted.")
|
|
if sys1.var != sys2.var:
|
|
raise ValueError("Both `sys1` and `sys2` should be using the"
|
|
" same complex variable.")
|
|
|
|
return super().__new__(cls, sys1, sys2, _sympify(sign))
|
|
|
|
@property
|
|
def sys1(self):
|
|
r"""
|
|
Returns the system placed on the feedforward path of the MIMO feedback interconnection.
|
|
|
|
Examples
|
|
========
|
|
|
|
>>> from sympy import pprint
|
|
>>> from sympy.abc import s
|
|
>>> from sympy.physics.control.lti import TransferFunction, TransferFunctionMatrix, MIMOFeedback
|
|
>>> tf1 = TransferFunction(s**2 + s + 1, s**2 - s + 1, s)
|
|
>>> tf2 = TransferFunction(1, s, s)
|
|
>>> tf3 = TransferFunction(1, 1, s)
|
|
>>> sys1 = TransferFunctionMatrix([[tf1, tf2], [tf2, tf1]])
|
|
>>> sys2 = TransferFunctionMatrix([[tf3, tf3], [tf3, tf2]])
|
|
>>> F_1 = MIMOFeedback(sys1, sys2, 1)
|
|
>>> F_1.sys1
|
|
TransferFunctionMatrix(((TransferFunction(s**2 + s + 1, s**2 - s + 1, s), TransferFunction(1, s, s)), (TransferFunction(1, s, s), TransferFunction(s**2 + s + 1, s**2 - s + 1, s))))
|
|
>>> pprint(_, use_unicode=False)
|
|
[ 2 ]
|
|
[s + s + 1 1 ]
|
|
[---------- - ]
|
|
[ 2 s ]
|
|
[s - s + 1 ]
|
|
[ ]
|
|
[ 2 ]
|
|
[ 1 s + s + 1]
|
|
[ - ----------]
|
|
[ s 2 ]
|
|
[ s - s + 1]{t}
|
|
|
|
"""
|
|
return self.args[0]
|
|
|
|
@property
|
|
def sys2(self):
|
|
r"""
|
|
Returns the feedback controller of the MIMO feedback interconnection.
|
|
|
|
Examples
|
|
========
|
|
|
|
>>> from sympy import pprint
|
|
>>> from sympy.abc import s
|
|
>>> from sympy.physics.control.lti import TransferFunction, TransferFunctionMatrix, MIMOFeedback
|
|
>>> tf1 = TransferFunction(s**2, s**3 - s + 1, s)
|
|
>>> tf2 = TransferFunction(1, s, s)
|
|
>>> tf3 = TransferFunction(1, 1, s)
|
|
>>> sys1 = TransferFunctionMatrix([[tf1, tf2], [tf2, tf1]])
|
|
>>> sys2 = TransferFunctionMatrix([[tf1, tf3], [tf3, tf2]])
|
|
>>> F_1 = MIMOFeedback(sys1, sys2)
|
|
>>> F_1.sys2
|
|
TransferFunctionMatrix(((TransferFunction(s**2, s**3 - s + 1, s), TransferFunction(1, 1, s)), (TransferFunction(1, 1, s), TransferFunction(1, s, s))))
|
|
>>> pprint(_, use_unicode=False)
|
|
[ 2 ]
|
|
[ s 1]
|
|
[---------- -]
|
|
[ 3 1]
|
|
[s - s + 1 ]
|
|
[ ]
|
|
[ 1 1]
|
|
[ - -]
|
|
[ 1 s]{t}
|
|
|
|
"""
|
|
return self.args[1]
|
|
|
|
@property
|
|
def var(self):
|
|
r"""
|
|
Returns the complex variable of the Laplace transform used by all
|
|
the transfer functions involved in the MIMO feedback loop.
|
|
|
|
Examples
|
|
========
|
|
|
|
>>> from sympy.abc import p
|
|
>>> from sympy.physics.control.lti import TransferFunction, TransferFunctionMatrix, MIMOFeedback
|
|
>>> tf1 = TransferFunction(p, 1 - p, p)
|
|
>>> tf2 = TransferFunction(1, p, p)
|
|
>>> tf3 = TransferFunction(1, 1, p)
|
|
>>> sys1 = TransferFunctionMatrix([[tf1, tf2], [tf2, tf1]])
|
|
>>> sys2 = TransferFunctionMatrix([[tf1, tf3], [tf3, tf2]])
|
|
>>> F_1 = MIMOFeedback(sys1, sys2, 1) # Positive feedback
|
|
>>> F_1.var
|
|
p
|
|
|
|
"""
|
|
return self.sys1.var
|
|
|
|
@property
|
|
def sign(self):
|
|
r"""
|
|
Returns the type of feedback interconnection of two models. ``1``
|
|
for Positive and ``-1`` for Negative.
|
|
"""
|
|
return self.args[2]
|
|
|
|
@property
|
|
def sensitivity(self):
|
|
r"""
|
|
Returns the sensitivity function matrix of the feedback loop.
|
|
|
|
Sensitivity of a closed-loop system is the ratio of change
|
|
in the open loop gain to the change in the closed loop gain.
|
|
|
|
.. note::
|
|
This method would not return the complementary
|
|
sensitivity function.
|
|
|
|
Examples
|
|
========
|
|
|
|
>>> from sympy import pprint
|
|
>>> from sympy.abc import p
|
|
>>> from sympy.physics.control.lti import TransferFunction, TransferFunctionMatrix, MIMOFeedback
|
|
>>> tf1 = TransferFunction(p, 1 - p, p)
|
|
>>> tf2 = TransferFunction(1, p, p)
|
|
>>> tf3 = TransferFunction(1, 1, p)
|
|
>>> sys1 = TransferFunctionMatrix([[tf1, tf2], [tf2, tf1]])
|
|
>>> sys2 = TransferFunctionMatrix([[tf1, tf3], [tf3, tf2]])
|
|
>>> F_1 = MIMOFeedback(sys1, sys2, 1) # Positive feedback
|
|
>>> F_2 = MIMOFeedback(sys1, sys2) # Negative feedback
|
|
>>> pprint(F_1.sensitivity, use_unicode=False)
|
|
[ 4 3 2 5 4 2 ]
|
|
[- p + 3*p - 4*p + 3*p - 1 p - 2*p + 3*p - 3*p + 1 ]
|
|
[---------------------------- -----------------------------]
|
|
[ 4 3 2 5 4 3 2 ]
|
|
[ p + 3*p - 8*p + 8*p - 3 p + 3*p - 8*p + 8*p - 3*p]
|
|
[ ]
|
|
[ 4 3 2 3 2 ]
|
|
[ p - p - p + p 3*p - 6*p + 4*p - 1 ]
|
|
[ -------------------------- -------------------------- ]
|
|
[ 4 3 2 4 3 2 ]
|
|
[ p + 3*p - 8*p + 8*p - 3 p + 3*p - 8*p + 8*p - 3 ]
|
|
>>> pprint(F_2.sensitivity, use_unicode=False)
|
|
[ 4 3 2 5 4 2 ]
|
|
[p - 3*p + 2*p + p - 1 p - 2*p + 3*p - 3*p + 1]
|
|
[------------------------ --------------------------]
|
|
[ 4 3 5 4 2 ]
|
|
[ p - 3*p + 2*p - 1 p - 3*p + 2*p - p ]
|
|
[ ]
|
|
[ 4 3 2 4 3 ]
|
|
[ p - p - p + p 2*p - 3*p + 2*p - 1 ]
|
|
[ ------------------- --------------------- ]
|
|
[ 4 3 4 3 ]
|
|
[ p - 3*p + 2*p - 1 p - 3*p + 2*p - 1 ]
|
|
|
|
"""
|
|
_sys1_mat = self.sys1.doit()._expr_mat
|
|
_sys2_mat = self.sys2.doit()._expr_mat
|
|
|
|
return (eye(self.sys1.num_inputs) - \
|
|
self.sign*_sys1_mat*_sys2_mat).inv()
|
|
|
|
def doit(self, cancel=True, expand=False, **kwargs):
|
|
r"""
|
|
Returns the resultant transfer function matrix obtained by the
|
|
feedback interconnection.
|
|
|
|
Examples
|
|
========
|
|
|
|
>>> from sympy import pprint
|
|
>>> from sympy.abc import s
|
|
>>> from sympy.physics.control.lti import TransferFunction, TransferFunctionMatrix, MIMOFeedback
|
|
>>> tf1 = TransferFunction(s, 1 - s, s)
|
|
>>> tf2 = TransferFunction(1, s, s)
|
|
>>> tf3 = TransferFunction(5, 1, s)
|
|
>>> tf4 = TransferFunction(s - 1, s, s)
|
|
>>> tf5 = TransferFunction(0, 1, s)
|
|
>>> sys1 = TransferFunctionMatrix([[tf1, tf2], [tf3, tf4]])
|
|
>>> sys2 = TransferFunctionMatrix([[tf3, tf5], [tf5, tf5]])
|
|
>>> F_1 = MIMOFeedback(sys1, sys2, 1)
|
|
>>> pprint(F_1, use_unicode=False)
|
|
/ [ s 1 ] [5 0] \-1 [ s 1 ]
|
|
| [----- - ] [- -] | [----- - ]
|
|
| [1 - s s ] [1 1] | [1 - s s ]
|
|
|I - [ ] *[ ] | * [ ]
|
|
| [ 5 s - 1] [0 0] | [ 5 s - 1]
|
|
| [ - -----] [- -] | [ - -----]
|
|
\ [ 1 s ]{t} [1 1]{t}/ [ 1 s ]{t}
|
|
>>> pprint(F_1.doit(), use_unicode=False)
|
|
[ -s 1 - s ]
|
|
[ ------- ----------- ]
|
|
[ 6*s - 1 s*(1 - 6*s) ]
|
|
[ ]
|
|
[25*s*(s - 1) + 5*(1 - s)*(6*s - 1) (s - 1)*(6*s + 24)]
|
|
[---------------------------------- ------------------]
|
|
[ (1 - s)*(6*s - 1) s*(6*s - 1) ]{t}
|
|
|
|
If the user wants the resultant ``TransferFunctionMatrix`` object without
|
|
canceling the common factors then the ``cancel`` kwarg should be passed ``False``.
|
|
|
|
>>> pprint(F_1.doit(cancel=False), use_unicode=False)
|
|
[ 25*s*(1 - s) 25 - 25*s ]
|
|
[ -------------------- -------------- ]
|
|
[ 25*(1 - 6*s)*(1 - s) 25*s*(1 - 6*s) ]
|
|
[ ]
|
|
[s*(25*s - 25) + 5*(1 - s)*(6*s - 1) s*(s - 1)*(6*s - 1) + s*(25*s - 25)]
|
|
[----------------------------------- -----------------------------------]
|
|
[ (1 - s)*(6*s - 1) 2 ]
|
|
[ s *(6*s - 1) ]{t}
|
|
|
|
If the user wants the expanded form of the resultant transfer function matrix,
|
|
the ``expand`` kwarg should be passed as ``True``.
|
|
|
|
>>> pprint(F_1.doit(expand=True), use_unicode=False)
|
|
[ -s 1 - s ]
|
|
[ ------- ---------- ]
|
|
[ 6*s - 1 2 ]
|
|
[ - 6*s + s ]
|
|
[ ]
|
|
[ 2 2 ]
|
|
[- 5*s + 10*s - 5 6*s + 18*s - 24]
|
|
[----------------- ----------------]
|
|
[ 2 2 ]
|
|
[ - 6*s + 7*s - 1 6*s - s ]{t}
|
|
|
|
"""
|
|
_mat = self.sensitivity * self.sys1.doit()._expr_mat
|
|
|
|
_resultant_tfm = _to_TFM(_mat, self.var)
|
|
|
|
if cancel:
|
|
_resultant_tfm = _resultant_tfm.simplify()
|
|
|
|
if expand:
|
|
_resultant_tfm = _resultant_tfm.expand()
|
|
|
|
return _resultant_tfm
|
|
|
|
def _eval_rewrite_as_TransferFunctionMatrix(self, sys1, sys2, sign, **kwargs):
|
|
return self.doit()
|
|
|
|
def __neg__(self):
|
|
return MIMOFeedback(-self.sys1, -self.sys2, self.sign)
|
|
|
|
|
|
def _to_TFM(mat, var):
|
|
"""Private method to convert ImmutableMatrix to TransferFunctionMatrix efficiently"""
|
|
to_tf = lambda expr: TransferFunction.from_rational_expression(expr, var)
|
|
arg = [[to_tf(expr) for expr in row] for row in mat.tolist()]
|
|
return TransferFunctionMatrix(arg)
|
|
|
|
|
|
class TransferFunctionMatrix(MIMOLinearTimeInvariant):
|
|
r"""
|
|
A class for representing the MIMO (multiple-input and multiple-output)
|
|
generalization of the SISO (single-input and single-output) transfer function.
|
|
|
|
It is a matrix of transfer functions (``TransferFunction``, SISO-``Series`` or SISO-``Parallel``).
|
|
There is only one argument, ``arg`` which is also the compulsory argument.
|
|
``arg`` is expected to be strictly of the type list of lists
|
|
which holds the transfer functions or reducible to transfer functions.
|
|
|
|
Parameters
|
|
==========
|
|
|
|
arg : Nested ``List`` (strictly).
|
|
Users are expected to input a nested list of ``TransferFunction``, ``Series``
|
|
and/or ``Parallel`` objects.
|
|
|
|
Examples
|
|
========
|
|
|
|
.. note::
|
|
``pprint()`` can be used for better visualization of ``TransferFunctionMatrix`` objects.
|
|
|
|
>>> from sympy.abc import s, p, a
|
|
>>> from sympy import pprint
|
|
>>> from sympy.physics.control.lti import TransferFunction, TransferFunctionMatrix, Series, Parallel
|
|
>>> tf_1 = TransferFunction(s + a, s**2 + s + 1, s)
|
|
>>> tf_2 = TransferFunction(p**4 - 3*p + 2, s + p, s)
|
|
>>> tf_3 = TransferFunction(3, s + 2, s)
|
|
>>> tf_4 = TransferFunction(-a + p, 9*s - 9, s)
|
|
>>> tfm_1 = TransferFunctionMatrix([[tf_1], [tf_2], [tf_3]])
|
|
>>> tfm_1
|
|
TransferFunctionMatrix(((TransferFunction(a + s, s**2 + s + 1, s),), (TransferFunction(p**4 - 3*p + 2, p + s, s),), (TransferFunction(3, s + 2, s),)))
|
|
>>> tfm_1.var
|
|
s
|
|
>>> tfm_1.num_inputs
|
|
1
|
|
>>> tfm_1.num_outputs
|
|
3
|
|
>>> tfm_1.shape
|
|
(3, 1)
|
|
>>> tfm_1.args
|
|
(((TransferFunction(a + s, s**2 + s + 1, s),), (TransferFunction(p**4 - 3*p + 2, p + s, s),), (TransferFunction(3, s + 2, s),)),)
|
|
>>> tfm_2 = TransferFunctionMatrix([[tf_1, -tf_3], [tf_2, -tf_1], [tf_3, -tf_2]])
|
|
>>> tfm_2
|
|
TransferFunctionMatrix(((TransferFunction(a + s, s**2 + s + 1, s), TransferFunction(-3, s + 2, s)), (TransferFunction(p**4 - 3*p + 2, p + s, s), TransferFunction(-a - s, s**2 + s + 1, s)), (TransferFunction(3, s + 2, s), TransferFunction(-p**4 + 3*p - 2, p + s, s))))
|
|
>>> pprint(tfm_2, use_unicode=False) # pretty-printing for better visualization
|
|
[ a + s -3 ]
|
|
[ ---------- ----- ]
|
|
[ 2 s + 2 ]
|
|
[ s + s + 1 ]
|
|
[ ]
|
|
[ 4 ]
|
|
[p - 3*p + 2 -a - s ]
|
|
[------------ ---------- ]
|
|
[ p + s 2 ]
|
|
[ s + s + 1 ]
|
|
[ ]
|
|
[ 4 ]
|
|
[ 3 - p + 3*p - 2]
|
|
[ ----- --------------]
|
|
[ s + 2 p + s ]{t}
|
|
|
|
TransferFunctionMatrix can be transposed, if user wants to switch the input and output transfer functions
|
|
|
|
>>> tfm_2.transpose()
|
|
TransferFunctionMatrix(((TransferFunction(a + s, s**2 + s + 1, s), TransferFunction(p**4 - 3*p + 2, p + s, s), TransferFunction(3, s + 2, s)), (TransferFunction(-3, s + 2, s), TransferFunction(-a - s, s**2 + s + 1, s), TransferFunction(-p**4 + 3*p - 2, p + s, s))))
|
|
>>> pprint(_, use_unicode=False)
|
|
[ 4 ]
|
|
[ a + s p - 3*p + 2 3 ]
|
|
[---------- ------------ ----- ]
|
|
[ 2 p + s s + 2 ]
|
|
[s + s + 1 ]
|
|
[ ]
|
|
[ 4 ]
|
|
[ -3 -a - s - p + 3*p - 2]
|
|
[ ----- ---------- --------------]
|
|
[ s + 2 2 p + s ]
|
|
[ s + s + 1 ]{t}
|
|
|
|
>>> tf_5 = TransferFunction(5, s, s)
|
|
>>> tf_6 = TransferFunction(5*s, (2 + s**2), s)
|
|
>>> tf_7 = TransferFunction(5, (s*(2 + s**2)), s)
|
|
>>> tf_8 = TransferFunction(5, 1, s)
|
|
>>> tfm_3 = TransferFunctionMatrix([[tf_5, tf_6], [tf_7, tf_8]])
|
|
>>> tfm_3
|
|
TransferFunctionMatrix(((TransferFunction(5, s, s), TransferFunction(5*s, s**2 + 2, s)), (TransferFunction(5, s*(s**2 + 2), s), TransferFunction(5, 1, s))))
|
|
>>> pprint(tfm_3, use_unicode=False)
|
|
[ 5 5*s ]
|
|
[ - ------]
|
|
[ s 2 ]
|
|
[ s + 2]
|
|
[ ]
|
|
[ 5 5 ]
|
|
[---------- - ]
|
|
[ / 2 \ 1 ]
|
|
[s*\s + 2/ ]{t}
|
|
>>> tfm_3.var
|
|
s
|
|
>>> tfm_3.shape
|
|
(2, 2)
|
|
>>> tfm_3.num_outputs
|
|
2
|
|
>>> tfm_3.num_inputs
|
|
2
|
|
>>> tfm_3.args
|
|
(((TransferFunction(5, s, s), TransferFunction(5*s, s**2 + 2, s)), (TransferFunction(5, s*(s**2 + 2), s), TransferFunction(5, 1, s))),)
|
|
|
|
To access the ``TransferFunction`` at any index in the ``TransferFunctionMatrix``, use the index notation.
|
|
|
|
>>> tfm_3[1, 0] # gives the TransferFunction present at 2nd Row and 1st Col. Similar to that in Matrix classes
|
|
TransferFunction(5, s*(s**2 + 2), s)
|
|
>>> tfm_3[0, 0] # gives the TransferFunction present at 1st Row and 1st Col.
|
|
TransferFunction(5, s, s)
|
|
>>> tfm_3[:, 0] # gives the first column
|
|
TransferFunctionMatrix(((TransferFunction(5, s, s),), (TransferFunction(5, s*(s**2 + 2), s),)))
|
|
>>> pprint(_, use_unicode=False)
|
|
[ 5 ]
|
|
[ - ]
|
|
[ s ]
|
|
[ ]
|
|
[ 5 ]
|
|
[----------]
|
|
[ / 2 \]
|
|
[s*\s + 2/]{t}
|
|
>>> tfm_3[0, :] # gives the first row
|
|
TransferFunctionMatrix(((TransferFunction(5, s, s), TransferFunction(5*s, s**2 + 2, s)),))
|
|
>>> pprint(_, use_unicode=False)
|
|
[5 5*s ]
|
|
[- ------]
|
|
[s 2 ]
|
|
[ s + 2]{t}
|
|
|
|
To negate a transfer function matrix, ``-`` operator can be prepended:
|
|
|
|
>>> tfm_4 = TransferFunctionMatrix([[tf_2], [-tf_1], [tf_3]])
|
|
>>> -tfm_4
|
|
TransferFunctionMatrix(((TransferFunction(-p**4 + 3*p - 2, p + s, s),), (TransferFunction(a + s, s**2 + s + 1, s),), (TransferFunction(-3, s + 2, s),)))
|
|
>>> tfm_5 = TransferFunctionMatrix([[tf_1, tf_2], [tf_3, -tf_1]])
|
|
>>> -tfm_5
|
|
TransferFunctionMatrix(((TransferFunction(-a - s, s**2 + s + 1, s), TransferFunction(-p**4 + 3*p - 2, p + s, s)), (TransferFunction(-3, s + 2, s), TransferFunction(a + s, s**2 + s + 1, s))))
|
|
|
|
``subs()`` returns the ``TransferFunctionMatrix`` object with the value substituted in the expression. This will not
|
|
mutate your original ``TransferFunctionMatrix``.
|
|
|
|
>>> tfm_2.subs(p, 2) # substituting p everywhere in tfm_2 with 2.
|
|
TransferFunctionMatrix(((TransferFunction(a + s, s**2 + s + 1, s), TransferFunction(-3, s + 2, s)), (TransferFunction(12, s + 2, s), TransferFunction(-a - s, s**2 + s + 1, s)), (TransferFunction(3, s + 2, s), TransferFunction(-12, s + 2, s))))
|
|
>>> pprint(_, use_unicode=False)
|
|
[ a + s -3 ]
|
|
[---------- ----- ]
|
|
[ 2 s + 2 ]
|
|
[s + s + 1 ]
|
|
[ ]
|
|
[ 12 -a - s ]
|
|
[ ----- ----------]
|
|
[ s + 2 2 ]
|
|
[ s + s + 1]
|
|
[ ]
|
|
[ 3 -12 ]
|
|
[ ----- ----- ]
|
|
[ s + 2 s + 2 ]{t}
|
|
>>> pprint(tfm_2, use_unicode=False) # State of tfm_2 is unchanged after substitution
|
|
[ a + s -3 ]
|
|
[ ---------- ----- ]
|
|
[ 2 s + 2 ]
|
|
[ s + s + 1 ]
|
|
[ ]
|
|
[ 4 ]
|
|
[p - 3*p + 2 -a - s ]
|
|
[------------ ---------- ]
|
|
[ p + s 2 ]
|
|
[ s + s + 1 ]
|
|
[ ]
|
|
[ 4 ]
|
|
[ 3 - p + 3*p - 2]
|
|
[ ----- --------------]
|
|
[ s + 2 p + s ]{t}
|
|
|
|
``subs()`` also supports multiple substitutions.
|
|
|
|
>>> tfm_2.subs({p: 2, a: 1}) # substituting p with 2 and a with 1
|
|
TransferFunctionMatrix(((TransferFunction(s + 1, s**2 + s + 1, s), TransferFunction(-3, s + 2, s)), (TransferFunction(12, s + 2, s), TransferFunction(-s - 1, s**2 + s + 1, s)), (TransferFunction(3, s + 2, s), TransferFunction(-12, s + 2, s))))
|
|
>>> pprint(_, use_unicode=False)
|
|
[ s + 1 -3 ]
|
|
[---------- ----- ]
|
|
[ 2 s + 2 ]
|
|
[s + s + 1 ]
|
|
[ ]
|
|
[ 12 -s - 1 ]
|
|
[ ----- ----------]
|
|
[ s + 2 2 ]
|
|
[ s + s + 1]
|
|
[ ]
|
|
[ 3 -12 ]
|
|
[ ----- ----- ]
|
|
[ s + 2 s + 2 ]{t}
|
|
|
|
Users can reduce the ``Series`` and ``Parallel`` elements of the matrix to ``TransferFunction`` by using
|
|
``doit()``.
|
|
|
|
>>> tfm_6 = TransferFunctionMatrix([[Series(tf_3, tf_4), Parallel(tf_3, tf_4)]])
|
|
>>> tfm_6
|
|
TransferFunctionMatrix(((Series(TransferFunction(3, s + 2, s), TransferFunction(-a + p, 9*s - 9, s)), Parallel(TransferFunction(3, s + 2, s), TransferFunction(-a + p, 9*s - 9, s))),))
|
|
>>> pprint(tfm_6, use_unicode=False)
|
|
[ -a + p 3 -a + p 3 ]
|
|
[-------*----- ------- + -----]
|
|
[9*s - 9 s + 2 9*s - 9 s + 2]{t}
|
|
>>> tfm_6.doit()
|
|
TransferFunctionMatrix(((TransferFunction(-3*a + 3*p, (s + 2)*(9*s - 9), s), TransferFunction(27*s + (-a + p)*(s + 2) - 27, (s + 2)*(9*s - 9), s)),))
|
|
>>> pprint(_, use_unicode=False)
|
|
[ -3*a + 3*p 27*s + (-a + p)*(s + 2) - 27]
|
|
[----------------- ----------------------------]
|
|
[(s + 2)*(9*s - 9) (s + 2)*(9*s - 9) ]{t}
|
|
>>> tf_9 = TransferFunction(1, s, s)
|
|
>>> tf_10 = TransferFunction(1, s**2, s)
|
|
>>> tfm_7 = TransferFunctionMatrix([[Series(tf_9, tf_10), tf_9], [tf_10, Parallel(tf_9, tf_10)]])
|
|
>>> tfm_7
|
|
TransferFunctionMatrix(((Series(TransferFunction(1, s, s), TransferFunction(1, s**2, s)), TransferFunction(1, s, s)), (TransferFunction(1, s**2, s), Parallel(TransferFunction(1, s, s), TransferFunction(1, s**2, s)))))
|
|
>>> pprint(tfm_7, use_unicode=False)
|
|
[ 1 1 ]
|
|
[---- - ]
|
|
[ 2 s ]
|
|
[s*s ]
|
|
[ ]
|
|
[ 1 1 1]
|
|
[ -- -- + -]
|
|
[ 2 2 s]
|
|
[ s s ]{t}
|
|
>>> tfm_7.doit()
|
|
TransferFunctionMatrix(((TransferFunction(1, s**3, s), TransferFunction(1, s, s)), (TransferFunction(1, s**2, s), TransferFunction(s**2 + s, s**3, s))))
|
|
>>> pprint(_, use_unicode=False)
|
|
[1 1 ]
|
|
[-- - ]
|
|
[ 3 s ]
|
|
[s ]
|
|
[ ]
|
|
[ 2 ]
|
|
[1 s + s]
|
|
[-- ------]
|
|
[ 2 3 ]
|
|
[s s ]{t}
|
|
|
|
Addition, subtraction, and multiplication of transfer function matrices can form
|
|
unevaluated ``Series`` or ``Parallel`` objects.
|
|
|
|
- For addition and subtraction:
|
|
All the transfer function matrices must have the same shape.
|
|
|
|
- For multiplication (C = A * B):
|
|
The number of inputs of the first transfer function matrix (A) must be equal to the
|
|
number of outputs of the second transfer function matrix (B).
|
|
|
|
Also, use pretty-printing (``pprint``) to analyse better.
|
|
|
|
>>> tfm_8 = TransferFunctionMatrix([[tf_3], [tf_2], [-tf_1]])
|
|
>>> tfm_9 = TransferFunctionMatrix([[-tf_3]])
|
|
>>> tfm_10 = TransferFunctionMatrix([[tf_1], [tf_2], [tf_4]])
|
|
>>> tfm_11 = TransferFunctionMatrix([[tf_4], [-tf_1]])
|
|
>>> tfm_12 = TransferFunctionMatrix([[tf_4, -tf_1, tf_3], [-tf_2, -tf_4, -tf_3]])
|
|
>>> tfm_8 + tfm_10
|
|
MIMOParallel(TransferFunctionMatrix(((TransferFunction(3, s + 2, s),), (TransferFunction(p**4 - 3*p + 2, p + s, s),), (TransferFunction(-a - s, s**2 + s + 1, s),))), TransferFunctionMatrix(((TransferFunction(a + s, s**2 + s + 1, s),), (TransferFunction(p**4 - 3*p + 2, p + s, s),), (TransferFunction(-a + p, 9*s - 9, s),))))
|
|
>>> pprint(_, use_unicode=False)
|
|
[ 3 ] [ a + s ]
|
|
[ ----- ] [ ---------- ]
|
|
[ s + 2 ] [ 2 ]
|
|
[ ] [ s + s + 1 ]
|
|
[ 4 ] [ ]
|
|
[p - 3*p + 2] [ 4 ]
|
|
[------------] + [p - 3*p + 2]
|
|
[ p + s ] [------------]
|
|
[ ] [ p + s ]
|
|
[ -a - s ] [ ]
|
|
[ ---------- ] [ -a + p ]
|
|
[ 2 ] [ ------- ]
|
|
[ s + s + 1 ]{t} [ 9*s - 9 ]{t}
|
|
>>> -tfm_10 - tfm_8
|
|
MIMOParallel(TransferFunctionMatrix(((TransferFunction(-a - s, s**2 + s + 1, s),), (TransferFunction(-p**4 + 3*p - 2, p + s, s),), (TransferFunction(a - p, 9*s - 9, s),))), TransferFunctionMatrix(((TransferFunction(-3, s + 2, s),), (TransferFunction(-p**4 + 3*p - 2, p + s, s),), (TransferFunction(a + s, s**2 + s + 1, s),))))
|
|
>>> pprint(_, use_unicode=False)
|
|
[ -a - s ] [ -3 ]
|
|
[ ---------- ] [ ----- ]
|
|
[ 2 ] [ s + 2 ]
|
|
[ s + s + 1 ] [ ]
|
|
[ ] [ 4 ]
|
|
[ 4 ] [- p + 3*p - 2]
|
|
[- p + 3*p - 2] + [--------------]
|
|
[--------------] [ p + s ]
|
|
[ p + s ] [ ]
|
|
[ ] [ a + s ]
|
|
[ a - p ] [ ---------- ]
|
|
[ ------- ] [ 2 ]
|
|
[ 9*s - 9 ]{t} [ s + s + 1 ]{t}
|
|
>>> tfm_12 * tfm_8
|
|
MIMOSeries(TransferFunctionMatrix(((TransferFunction(3, s + 2, s),), (TransferFunction(p**4 - 3*p + 2, p + s, s),), (TransferFunction(-a - s, s**2 + s + 1, s),))), TransferFunctionMatrix(((TransferFunction(-a + p, 9*s - 9, s), TransferFunction(-a - s, s**2 + s + 1, s), TransferFunction(3, s + 2, s)), (TransferFunction(-p**4 + 3*p - 2, p + s, s), TransferFunction(a - p, 9*s - 9, s), TransferFunction(-3, s + 2, s)))))
|
|
>>> pprint(_, use_unicode=False)
|
|
[ 3 ]
|
|
[ ----- ]
|
|
[ -a + p -a - s 3 ] [ s + 2 ]
|
|
[ ------- ---------- -----] [ ]
|
|
[ 9*s - 9 2 s + 2] [ 4 ]
|
|
[ s + s + 1 ] [p - 3*p + 2]
|
|
[ ] *[------------]
|
|
[ 4 ] [ p + s ]
|
|
[- p + 3*p - 2 a - p -3 ] [ ]
|
|
[-------------- ------- -----] [ -a - s ]
|
|
[ p + s 9*s - 9 s + 2]{t} [ ---------- ]
|
|
[ 2 ]
|
|
[ s + s + 1 ]{t}
|
|
>>> tfm_12 * tfm_8 * tfm_9
|
|
MIMOSeries(TransferFunctionMatrix(((TransferFunction(-3, s + 2, s),),)), TransferFunctionMatrix(((TransferFunction(3, s + 2, s),), (TransferFunction(p**4 - 3*p + 2, p + s, s),), (TransferFunction(-a - s, s**2 + s + 1, s),))), TransferFunctionMatrix(((TransferFunction(-a + p, 9*s - 9, s), TransferFunction(-a - s, s**2 + s + 1, s), TransferFunction(3, s + 2, s)), (TransferFunction(-p**4 + 3*p - 2, p + s, s), TransferFunction(a - p, 9*s - 9, s), TransferFunction(-3, s + 2, s)))))
|
|
>>> pprint(_, use_unicode=False)
|
|
[ 3 ]
|
|
[ ----- ]
|
|
[ -a + p -a - s 3 ] [ s + 2 ]
|
|
[ ------- ---------- -----] [ ]
|
|
[ 9*s - 9 2 s + 2] [ 4 ]
|
|
[ s + s + 1 ] [p - 3*p + 2] [ -3 ]
|
|
[ ] *[------------] *[-----]
|
|
[ 4 ] [ p + s ] [s + 2]{t}
|
|
[- p + 3*p - 2 a - p -3 ] [ ]
|
|
[-------------- ------- -----] [ -a - s ]
|
|
[ p + s 9*s - 9 s + 2]{t} [ ---------- ]
|
|
[ 2 ]
|
|
[ s + s + 1 ]{t}
|
|
>>> tfm_10 + tfm_8*tfm_9
|
|
MIMOParallel(TransferFunctionMatrix(((TransferFunction(a + s, s**2 + s + 1, s),), (TransferFunction(p**4 - 3*p + 2, p + s, s),), (TransferFunction(-a + p, 9*s - 9, s),))), MIMOSeries(TransferFunctionMatrix(((TransferFunction(-3, s + 2, s),),)), TransferFunctionMatrix(((TransferFunction(3, s + 2, s),), (TransferFunction(p**4 - 3*p + 2, p + s, s),), (TransferFunction(-a - s, s**2 + s + 1, s),)))))
|
|
>>> pprint(_, use_unicode=False)
|
|
[ a + s ] [ 3 ]
|
|
[ ---------- ] [ ----- ]
|
|
[ 2 ] [ s + 2 ]
|
|
[ s + s + 1 ] [ ]
|
|
[ ] [ 4 ]
|
|
[ 4 ] [p - 3*p + 2] [ -3 ]
|
|
[p - 3*p + 2] + [------------] *[-----]
|
|
[------------] [ p + s ] [s + 2]{t}
|
|
[ p + s ] [ ]
|
|
[ ] [ -a - s ]
|
|
[ -a + p ] [ ---------- ]
|
|
[ ------- ] [ 2 ]
|
|
[ 9*s - 9 ]{t} [ s + s + 1 ]{t}
|
|
|
|
These unevaluated ``Series`` or ``Parallel`` objects can convert into the
|
|
resultant transfer function matrix using ``.doit()`` method or by
|
|
``.rewrite(TransferFunctionMatrix)``.
|
|
|
|
>>> (-tfm_8 + tfm_10 + tfm_8*tfm_9).doit()
|
|
TransferFunctionMatrix(((TransferFunction((a + s)*(s + 2)**3 - 3*(s + 2)**2*(s**2 + s + 1) - 9*(s + 2)*(s**2 + s + 1), (s + 2)**3*(s**2 + s + 1), s),), (TransferFunction((p + s)*(-3*p**4 + 9*p - 6), (p + s)**2*(s + 2), s),), (TransferFunction((-a + p)*(s + 2)*(s**2 + s + 1)**2 + (a + s)*(s + 2)*(9*s - 9)*(s**2 + s + 1) + (3*a + 3*s)*(9*s - 9)*(s**2 + s + 1), (s + 2)*(9*s - 9)*(s**2 + s + 1)**2, s),)))
|
|
>>> (-tfm_12 * -tfm_8 * -tfm_9).rewrite(TransferFunctionMatrix)
|
|
TransferFunctionMatrix(((TransferFunction(3*(-3*a + 3*p)*(p + s)*(s + 2)*(s**2 + s + 1)**2 + 3*(-3*a - 3*s)*(p + s)*(s + 2)*(9*s - 9)*(s**2 + s + 1) + 3*(a + s)*(s + 2)**2*(9*s - 9)*(-p**4 + 3*p - 2)*(s**2 + s + 1), (p + s)*(s + 2)**3*(9*s - 9)*(s**2 + s + 1)**2, s),), (TransferFunction(3*(-a + p)*(p + s)*(s + 2)**2*(-p**4 + 3*p - 2)*(s**2 + s + 1) + 3*(3*a + 3*s)*(p + s)**2*(s + 2)*(9*s - 9) + 3*(p + s)*(s + 2)*(9*s - 9)*(-3*p**4 + 9*p - 6)*(s**2 + s + 1), (p + s)**2*(s + 2)**3*(9*s - 9)*(s**2 + s + 1), s),)))
|
|
|
|
See Also
|
|
========
|
|
|
|
TransferFunction, MIMOSeries, MIMOParallel, Feedback
|
|
|
|
"""
|
|
def __new__(cls, arg):
|
|
|
|
expr_mat_arg = []
|
|
try:
|
|
var = arg[0][0].var
|
|
except TypeError:
|
|
raise ValueError("`arg` param in TransferFunctionMatrix should "
|
|
"strictly be a nested list containing TransferFunction objects.")
|
|
for row_index, row in enumerate(arg):
|
|
temp = []
|
|
for col_index, element in enumerate(row):
|
|
if not isinstance(element, SISOLinearTimeInvariant):
|
|
raise TypeError("Each element is expected to be of type `SISOLinearTimeInvariant`.")
|
|
|
|
if var != element.var:
|
|
raise ValueError("Conflicting value(s) found for `var`. All TransferFunction instances in "
|
|
"TransferFunctionMatrix should use the same complex variable in Laplace domain.")
|
|
|
|
temp.append(element.to_expr())
|
|
expr_mat_arg.append(temp)
|
|
|
|
if isinstance(arg, (list, Tuple)):
|
|
# Making nested Tuple (sympy.core.containers.Tuple) from nested list or nested python tuple
|
|
arg = Tuple(*(Tuple(*r, sympify=False) for r in arg), sympify=False)
|
|
|
|
obj = super(TransferFunctionMatrix, cls).__new__(cls, arg)
|
|
obj._expr_mat = ImmutableMatrix(expr_mat_arg)
|
|
return obj
|
|
|
|
@classmethod
|
|
def from_Matrix(cls, matrix, var):
|
|
"""
|
|
Creates a new ``TransferFunctionMatrix`` efficiently from a SymPy Matrix of ``Expr`` objects.
|
|
|
|
Parameters
|
|
==========
|
|
|
|
matrix : ``ImmutableMatrix`` having ``Expr``/``Number`` elements.
|
|
var : Symbol
|
|
Complex variable of the Laplace transform which will be used by the
|
|
all the ``TransferFunction`` objects in the ``TransferFunctionMatrix``.
|
|
|
|
Examples
|
|
========
|
|
|
|
>>> from sympy.abc import s
|
|
>>> from sympy.physics.control.lti import TransferFunctionMatrix
|
|
>>> from sympy import Matrix, pprint
|
|
>>> M = Matrix([[s, 1/s], [1/(s+1), s]])
|
|
>>> M_tf = TransferFunctionMatrix.from_Matrix(M, s)
|
|
>>> pprint(M_tf, use_unicode=False)
|
|
[ s 1]
|
|
[ - -]
|
|
[ 1 s]
|
|
[ ]
|
|
[ 1 s]
|
|
[----- -]
|
|
[s + 1 1]{t}
|
|
>>> M_tf.elem_poles()
|
|
[[[], [0]], [[-1], []]]
|
|
>>> M_tf.elem_zeros()
|
|
[[[0], []], [[], [0]]]
|
|
|
|
"""
|
|
return _to_TFM(matrix, var)
|
|
|
|
@property
|
|
def var(self):
|
|
"""
|
|
Returns the complex variable used by all the transfer functions or
|
|
``Series``/``Parallel`` objects in a transfer function matrix.
|
|
|
|
Examples
|
|
========
|
|
|
|
>>> from sympy.abc import p, s
|
|
>>> from sympy.physics.control.lti import TransferFunction, TransferFunctionMatrix, Series, Parallel
|
|
>>> G1 = TransferFunction(p**2 + 2*p + 4, p - 6, p)
|
|
>>> G2 = TransferFunction(p, 4 - p, p)
|
|
>>> G3 = TransferFunction(0, p**4 - 1, p)
|
|
>>> G4 = TransferFunction(s + 1, s**2 + s + 1, s)
|
|
>>> S1 = Series(G1, G2)
|
|
>>> S2 = Series(-G3, Parallel(G2, -G1))
|
|
>>> tfm1 = TransferFunctionMatrix([[G1], [G2], [G3]])
|
|
>>> tfm1.var
|
|
p
|
|
>>> tfm2 = TransferFunctionMatrix([[-S1, -S2], [S1, S2]])
|
|
>>> tfm2.var
|
|
p
|
|
>>> tfm3 = TransferFunctionMatrix([[G4]])
|
|
>>> tfm3.var
|
|
s
|
|
|
|
"""
|
|
return self.args[0][0][0].var
|
|
|
|
@property
|
|
def num_inputs(self):
|
|
"""
|
|
Returns the number of inputs of the system.
|
|
|
|
Examples
|
|
========
|
|
|
|
>>> from sympy.abc import s, p
|
|
>>> from sympy.physics.control.lti import TransferFunction, TransferFunctionMatrix
|
|
>>> G1 = TransferFunction(s + 3, s**2 - 3, s)
|
|
>>> G2 = TransferFunction(4, s**2, s)
|
|
>>> G3 = TransferFunction(p**2 + s**2, p - 3, s)
|
|
>>> tfm_1 = TransferFunctionMatrix([[G2, -G1, G3], [-G2, -G1, -G3]])
|
|
>>> tfm_1.num_inputs
|
|
3
|
|
|
|
See Also
|
|
========
|
|
|
|
num_outputs
|
|
|
|
"""
|
|
return self._expr_mat.shape[1]
|
|
|
|
@property
|
|
def num_outputs(self):
|
|
"""
|
|
Returns the number of outputs of the system.
|
|
|
|
Examples
|
|
========
|
|
|
|
>>> from sympy.abc import s
|
|
>>> from sympy.physics.control.lti import TransferFunctionMatrix
|
|
>>> from sympy import Matrix
|
|
>>> M_1 = Matrix([[s], [1/s]])
|
|
>>> TFM = TransferFunctionMatrix.from_Matrix(M_1, s)
|
|
>>> print(TFM)
|
|
TransferFunctionMatrix(((TransferFunction(s, 1, s),), (TransferFunction(1, s, s),)))
|
|
>>> TFM.num_outputs
|
|
2
|
|
|
|
See Also
|
|
========
|
|
|
|
num_inputs
|
|
|
|
"""
|
|
return self._expr_mat.shape[0]
|
|
|
|
@property
|
|
def shape(self):
|
|
"""
|
|
Returns the shape of the transfer function matrix, that is, ``(# of outputs, # of inputs)``.
|
|
|
|
Examples
|
|
========
|
|
|
|
>>> from sympy.abc import s, p
|
|
>>> from sympy.physics.control.lti import TransferFunction, TransferFunctionMatrix
|
|
>>> tf1 = TransferFunction(p**2 - 1, s**4 + s**3 - p, p)
|
|
>>> tf2 = TransferFunction(1 - p, p**2 - 3*p + 7, p)
|
|
>>> tf3 = TransferFunction(3, 4, p)
|
|
>>> tfm1 = TransferFunctionMatrix([[tf1, -tf2]])
|
|
>>> tfm1.shape
|
|
(1, 2)
|
|
>>> tfm2 = TransferFunctionMatrix([[-tf2, tf3], [tf1, -tf1]])
|
|
>>> tfm2.shape
|
|
(2, 2)
|
|
|
|
"""
|
|
return self._expr_mat.shape
|
|
|
|
def __neg__(self):
|
|
neg = -self._expr_mat
|
|
return _to_TFM(neg, self.var)
|
|
|
|
@_check_other_MIMO
|
|
def __add__(self, other):
|
|
|
|
if not isinstance(other, MIMOParallel):
|
|
return MIMOParallel(self, other)
|
|
other_arg_list = list(other.args)
|
|
return MIMOParallel(self, *other_arg_list)
|
|
|
|
@_check_other_MIMO
|
|
def __sub__(self, other):
|
|
return self + (-other)
|
|
|
|
@_check_other_MIMO
|
|
def __mul__(self, other):
|
|
|
|
if not isinstance(other, MIMOSeries):
|
|
return MIMOSeries(other, self)
|
|
other_arg_list = list(other.args)
|
|
return MIMOSeries(*other_arg_list, self)
|
|
|
|
def __getitem__(self, key):
|
|
trunc = self._expr_mat.__getitem__(key)
|
|
if isinstance(trunc, ImmutableMatrix):
|
|
return _to_TFM(trunc, self.var)
|
|
return TransferFunction.from_rational_expression(trunc, self.var)
|
|
|
|
def transpose(self):
|
|
"""Returns the transpose of the ``TransferFunctionMatrix`` (switched input and output layers)."""
|
|
transposed_mat = self._expr_mat.transpose()
|
|
return _to_TFM(transposed_mat, self.var)
|
|
|
|
def elem_poles(self):
|
|
"""
|
|
Returns the poles of each element of the ``TransferFunctionMatrix``.
|
|
|
|
.. note::
|
|
Actual poles of a MIMO system are NOT the poles of individual elements.
|
|
|
|
Examples
|
|
========
|
|
|
|
>>> from sympy.abc import s
|
|
>>> from sympy.physics.control.lti import TransferFunction, TransferFunctionMatrix
|
|
>>> tf_1 = TransferFunction(3, (s + 1), s)
|
|
>>> tf_2 = TransferFunction(s + 6, (s + 1)*(s + 2), s)
|
|
>>> tf_3 = TransferFunction(s + 3, s**2 + 3*s + 2, s)
|
|
>>> tf_4 = TransferFunction(s + 2, s**2 + 5*s - 10, s)
|
|
>>> tfm_1 = TransferFunctionMatrix([[tf_1, tf_2], [tf_3, tf_4]])
|
|
>>> tfm_1
|
|
TransferFunctionMatrix(((TransferFunction(3, s + 1, s), TransferFunction(s + 6, (s + 1)*(s + 2), s)), (TransferFunction(s + 3, s**2 + 3*s + 2, s), TransferFunction(s + 2, s**2 + 5*s - 10, s))))
|
|
>>> tfm_1.elem_poles()
|
|
[[[-1], [-2, -1]], [[-2, -1], [-5/2 + sqrt(65)/2, -sqrt(65)/2 - 5/2]]]
|
|
|
|
See Also
|
|
========
|
|
|
|
elem_zeros
|
|
|
|
"""
|
|
return [[element.poles() for element in row] for row in self.doit().args[0]]
|
|
|
|
def elem_zeros(self):
|
|
"""
|
|
Returns the zeros of each element of the ``TransferFunctionMatrix``.
|
|
|
|
.. note::
|
|
Actual zeros of a MIMO system are NOT the zeros of individual elements.
|
|
|
|
Examples
|
|
========
|
|
|
|
>>> from sympy.abc import s
|
|
>>> from sympy.physics.control.lti import TransferFunction, TransferFunctionMatrix
|
|
>>> tf_1 = TransferFunction(3, (s + 1), s)
|
|
>>> tf_2 = TransferFunction(s + 6, (s + 1)*(s + 2), s)
|
|
>>> tf_3 = TransferFunction(s + 3, s**2 + 3*s + 2, s)
|
|
>>> tf_4 = TransferFunction(s**2 - 9*s + 20, s**2 + 5*s - 10, s)
|
|
>>> tfm_1 = TransferFunctionMatrix([[tf_1, tf_2], [tf_3, tf_4]])
|
|
>>> tfm_1
|
|
TransferFunctionMatrix(((TransferFunction(3, s + 1, s), TransferFunction(s + 6, (s + 1)*(s + 2), s)), (TransferFunction(s + 3, s**2 + 3*s + 2, s), TransferFunction(s**2 - 9*s + 20, s**2 + 5*s - 10, s))))
|
|
>>> tfm_1.elem_zeros()
|
|
[[[], [-6]], [[-3], [4, 5]]]
|
|
|
|
See Also
|
|
========
|
|
|
|
elem_poles
|
|
|
|
"""
|
|
return [[element.zeros() for element in row] for row in self.doit().args[0]]
|
|
|
|
def _flat(self):
|
|
"""Returns flattened list of args in TransferFunctionMatrix"""
|
|
return [elem for tup in self.args[0] for elem in tup]
|
|
|
|
def _eval_evalf(self, prec):
|
|
"""Calls evalf() on each transfer function in the transfer function matrix"""
|
|
mat = self._expr_mat.applyfunc(lambda a: a.evalf(n=prec_to_dps(prec)))
|
|
return _to_TFM(mat, self.var)
|
|
|
|
def _eval_simplify(self, **kwargs):
|
|
"""Simplifies the transfer function matrix"""
|
|
simp_mat = self._expr_mat.applyfunc(lambda a: cancel(a, expand=False))
|
|
return _to_TFM(simp_mat, self.var)
|
|
|
|
def expand(self, **hints):
|
|
"""Expands the transfer function matrix"""
|
|
expand_mat = self._expr_mat.expand(**hints)
|
|
return _to_TFM(expand_mat, self.var)
|