control.StateSpace¶
- class control.StateSpace(A, B, C, D[, dt])¶
Bases:
control.lti.LTI
A class for representing state-space models.
The StateSpace class is used to represent state-space realizations of linear time-invariant (LTI) systems:
dx/dt = A x + B u y = C x + D u
where u is the input, y is the output, and x is the state.
- Parameters
A (array_like) – System matrices of the appropriate dimensions.
B (array_like) – System matrices of the appropriate dimensions.
C (array_like) – System matrices of the appropriate dimensions.
D (array_like) – System matrices of the appropriate dimensions.
dt (None, True or float, optional) – System timebase. 0 (default) indicates continuous time, True indicates discrete time with unspecified sampling time, positive number is discrete time with specified sampling time, None indicates unspecified timebase (either continuous or discrete time).
- ninputs, noutputs, nstates
Number of input, output and state variables.
- Type
int
- A, B, C, D
System matrices defining the input/output dynamics.
- Type
2D arrays
- dt¶
System timebase. 0 (default) indicates continuous time, True indicates discrete time with unspecified sampling time, positive number is discrete time with specified sampling time, None indicates unspecified timebase (either continuous or discrete time).
- Type
None, True or float
Notes
The main data members in the
StateSpace
class are the A, B, C, and D matrices. The class also keeps track of the number of states (i.e., the size of A). The data format used to store state space matrices is set using the value of config.defaults[‘use_numpy_matrix’]. If True (default), the state space elements are stored as numpy.matrix objects; otherwise they are numpy.ndarray objects. Theuse_numpy_matrix()
function can be used to set the storage type.A discrete time system is created by specifying a nonzero ‘timebase’, dt when the system is constructed:
dt = 0: continuous time system (default)
dt > 0: discrete time system with sampling period ‘dt’
dt = True: discrete time with unspecified sampling period
dt = None: no timebase specified
Systems must have compatible timebases in order to be combined. A discrete time system with unspecified sampling time (dt = True) can be combined with a system having a specified sampling time; the result will be a discrete time system with the sample time of the latter system. Similarly, a system with timebase None can be combined with a system having any timebase; the result will have the timebase of the latter system. The default value of dt can be changed by changing the value of
control.config.defaults['control.default_dt']
.A state space system is callable and returns the value of the transfer function evaluated at a point in the complex plane. See
__call__()
for a more detailed description.StateSpace instances have support for IPython LaTeX output, intended for pretty-printing in Jupyter notebooks. The LaTeX output can be configured using control.config.defaults[‘statesp.latex_num_format’] and control.config.defaults[‘statesp.latex_repr_type’]. The LaTeX output is tailored for MathJax, as used in Jupyter, and may look odd when typeset by non-MathJax LaTeX systems.
control.config.defaults[‘statesp.latex_num_format’] is a format string fragment, specifically the part of the format string after ‘{:’ used to convert floating-point numbers to strings. By default it is ‘.3g’.
control.config.defaults[‘statesp.latex_repr_type’] must either be ‘partitioned’ or ‘separate’. If ‘partitioned’, the A, B, C, D matrices are shown as a single, partitioned matrix; if ‘separate’, the matrices are shown separately.
Methods
Append a second model to the present model.
Natural frequency, damping ratio of system poles
Return the zero-frequency gain
Compute the dynamics of the system
Feedback interconnection between two LTI systems.
(deprecated) Evaluate transfer function at complex frequencies.
Evaluate the linear time-invariant system at an array of angular frequencies.
Evaluate system’s transfer function at complex frequency using Laub’s or Horner’s method.
Check to see if a system is a continuous-time system
Check to see if a system is a discrete-time system
Check to see if a system is single input, single output
Return the Linear Fractional Transformation.
Calculate a minimal realization, removes unobservable and uncontrollable states
Compute the output of the system
Compute the poles of a state space system.
Return a list of a list of
scipy.signal.lti
objects.Convert a continuous time system to discrete time
Evaluate system’s transfer function at complex frequency using Laub’s method from Slycot.
Compute the zeros of a state space system.
- A¶
Dynamics matrix.
- B¶
Input matrix.
- C¶
Output matrix.
- D¶
Direct term.
- __add__(other)¶
Add two LTI systems (parallel connection).
- __call__(x, squeeze=None, warn_infinite=True)¶
Evaluate system’s transfer function at complex frequency.
Returns the complex frequency response sys(x) where x is s for continuous-time systems and z for discrete-time systems.
To evaluate at a frequency omega in radians per second, enter
x = omega * 1j
, for continuous-time systems, orx = exp(1j * omega * dt)
for discrete-time systems. Or useStateSpace.frequency_response()
.- Parameters
x (complex or complex 1D array_like) – Complex frequencies
squeeze (bool, optional) – If squeeze=True, remove single-dimensional entries from the shape of the output even if the system is not SISO. If squeeze=False, keep all indices (output, input and, if omega is array_like, frequency) even if the system is SISO. The default value can be set using config.defaults[‘control.squeeze_frequency_response’].
warn_infinite (bool, optional) – If set to False, don’t warn if frequency response is infinite.
- Returns
fresp – The frequency response of the system. If the system is SISO and squeeze is not True, the shape of the array matches the shape of omega. If the system is not SISO or squeeze is False, the first two dimensions of the array are indices for the output and input and the remaining dimensions match omega. If
squeeze
is True then single-dimensional axes are removed.- Return type
complex ndarray
- __div__(other)¶
Divide two LTI systems.
- __getitem__(indices)¶
Array style access
- __mul__(other)¶
Multiply two LTI objects (serial connection).
- __neg__()¶
Negate a state space system.
- __radd__(other)¶
Right add two LTI systems (parallel connection).
- __rdiv__(other)¶
Right divide two LTI systems.
- __rmul__(other)¶
Right multiply two LTI objects (serial connection).
- __rsub__(other)¶
Right subtract two LTI systems.
- __sub__(other)¶
Subtract two LTI systems.
- append(other)¶
Append a second model to the present model.
The second model is converted to state-space if necessary, inputs and outputs are appended and their order is preserved
- damp()¶
Natural frequency, damping ratio of system poles
- Returns
wn (array) – Natural frequencies for each system pole
zeta (array) – Damping ratio for each system pole
poles (array) – Array of system poles
- dcgain(warn_infinite=False)¶
Return the zero-frequency gain
The zero-frequency gain of a continuous-time state-space system is given by:
and of a discrete-time state-space system by:
- Parameters
warn_infinite (bool, optional) – By default, don’t issue a warning message if the zero-frequency gain is infinite. Setting warn_infinite to generate the warning message.
- Returns
gain – Array or scalar value for SISO systems, depending on config.defaults[‘control.squeeze_frequency_response’]. The value of the array elements or the scalar is either the zero-frequency (or DC) gain, or inf, if the frequency response is singular.
For real valued systems, the empty imaginary part of the complex zero-frequency response is discarded and a real array or scalar is returned.
- Return type
(noutputs, ninputs) ndarray or scalar
- dynamics(t, x, u=None)¶
Compute the dynamics of the system
Given input u and state x, returns the dynamics of the state-space system. If the system is continuous, returns the time derivative dx/dt
dx/dt = A x + B u
where A and B are the state-space matrices of the system. If the system is discrete-time, returns the next value of x:
x[t+dt] = A x[t] + B u[t]
The inputs x and u must be of the correct length for the system.
The first argument t is ignored because
StateSpace
systems are time-invariant. It is included so that the dynamics can be passed to most numerical integrators, such asscipy.integrate.solve_ivp()
and for consistency withIOSystem
systems.- Parameters
t (float (ignored)) – time
x (array_like) – current state
u (array_like (optional)) – input, zero if omitted
- Returns
dx/dt or x[t+dt]
- Return type
ndarray
- feedback(other=1, sign=- 1)¶
Feedback interconnection between two LTI systems.
- freqresp(omega)¶
(deprecated) Evaluate transfer function at complex frequencies.
- frequency_response(omega, squeeze=None)¶
Evaluate the linear time-invariant system at an array of angular frequencies.
Reports the frequency response of the system,
G(j*omega) = mag*exp(j*phase)
for continuous time systems. For discrete time systems, the response is evaluated around the unit circle such that
G(exp(j*omega*dt)) = mag*exp(j*phase).
In general the system may be multiple input, multiple output (MIMO), where m = self.ninputs number of inputs and p = self.noutputs number of outputs.
- Parameters
omega (float or 1D array_like) – A list, tuple, array, or scalar value of frequencies in radians/sec at which the system will be evaluated.
squeeze (bool, optional) – If squeeze=True, remove single-dimensional entries from the shape of the output even if the system is not SISO. If squeeze=False, keep all indices (output, input and, if omega is array_like, frequency) even if the system is SISO. The default value can be set using config.defaults[‘control.squeeze_frequency_response’].
- Returns
mag (ndarray) – The magnitude (absolute value, not dB or log10) of the system frequency response. If the system is SISO and squeeze is not True, the array is 1D, indexed by frequency. If the system is not SISO or squeeze is False, the array is 3D, indexed by the output, input, and frequency. If
squeeze
is True then single-dimensional axes are removed.phase (ndarray) – The wrapped phase in radians of the system frequency response.
omega (ndarray) – The (sorted) frequencies at which the response was evaluated.
- horner(x, warn_infinite=True)¶
Evaluate system’s transfer function at complex frequency using Laub’s or Horner’s method.
Evaluates sys(x) where x is s for continuous-time systems and z for discrete-time systems.
Expects inputs and outputs to be formatted correctly. Use
sys(x)
for a more user-friendly interface.- Parameters
x (complex array_like or complex) – Complex frequencies
- Returns
output – Frequency response
- Return type
(self.noutputs, self.ninputs, len(x)) complex ndarray
Notes
Attempts to use Laub’s method from Slycot library, with a fall-back to python code.
- property inputs¶
Deprecated attribute; use
ninputs
instead.The
input
attribute was used to store the number of system inputs. It is no longer used. If you need access to the number of inputs for an LTI system, useninputs
.
- isctime(strict=False)¶
Check to see if a system is a continuous-time system
- Parameters
sys (LTI system) – System to be checked
strict (bool, optional) – If strict is True, make sure that timebase is not None. Default is False.
- isdtime(strict=False)¶
Check to see if a system is a discrete-time system
- Parameters
strict (bool, optional) – If strict is True, make sure that timebase is not None. Default is False.
- issiso()¶
Check to see if a system is single input, single output
- lft(other, nu=- 1, ny=- 1)¶
Return the Linear Fractional Transformation.
A definition of the LFT operator can be found in Appendix A.7, page 512 in the 2nd Edition, Multivariable Feedback Control by Sigurd Skogestad.
An alternative definition can be found here: https://www.mathworks.com/help/control/ref/lft.html
- Parameters
other (LTI) – The lower LTI system
ny (int, optional) – Dimension of (plant) measurement output.
nu (int, optional) – Dimension of (plant) control input.
- minreal(tol=0.0)¶
Calculate a minimal realization, removes unobservable and uncontrollable states
- ninputs¶
Number of system inputs.
- noutputs¶
Number of system outputs.
- nstates¶
Number of system states.
- output(t, x, u=None)¶
Compute the output of the system
Given input u and state x, returns the output y of the state-space system:
y = C x + D u
where A and B are the state-space matrices of the system.
The first argument t is ignored because
StateSpace
systems are time-invariant. It is included so that the dynamics can be passed to most numerical integrators, such as scipy’s integrate.solve_ivp and for consistency withIOSystem
systems.The inputs x and u must be of the correct length for the system.
- Parameters
t (float (ignored)) – time
x (array_like) – current state
u (array_like (optional)) – input (zero if omitted)
- Returns
y
- Return type
ndarray
- property outputs¶
Deprecated attribute; use
noutputs
instead.The
output
attribute was used to store the number of system outputs. It is no longer used. If you need access to the number of outputs for an LTI system, usenoutputs
.
- pole()¶
Compute the poles of a state space system.
- returnScipySignalLTI(strict=True)¶
Return a list of a list of
scipy.signal.lti
objects.For instance,
>>> out = ssobject.returnScipySignalLTI() >>> out[3][5]
is a
scipy.signal.lti
object corresponding to the transfer function from the 6th input to the 4th output.- Parameters
strict (bool, optional) –
- True (default):
The timebase ssobject.dt cannot be None; it must be continuous (0) or discrete (True or > 0).
- False:
If ssobject.dt is None, continuous time
scipy.signal.lti
objects are returned.
- Returns
out – continuous time (inheriting from
scipy.signal.lti
) or discrete time (inheriting fromscipy.signal.dlti
) SISO objects- Return type
list of list of
scipy.signal.StateSpace
- sample(Ts, method='zoh', alpha=None, prewarp_frequency=None)¶
Convert a continuous time system to discrete time
Creates a discrete-time system from a continuous-time system by sampling. Multiple methods of conversion are supported.
- Parameters
Ts (float) – Sampling period
method ({"gbt", "bilinear", "euler", "backward_diff", "zoh"}) –
Which method to use:
gbt: generalized bilinear transformation
bilinear: Tustin’s approximation (“gbt” with alpha=0.5)
euler: Euler (or forward differencing) method (“gbt” with alpha=0)
backward_diff: Backwards differencing (“gbt” with alpha=1.0)
zoh: zero-order hold (default)
alpha (float within [0, 1]) – The generalized bilinear transformation weighting parameter, which should only be specified with method=”gbt”, and is ignored otherwise
prewarp_frequency (float within [0, infinity)) – The frequency [rad/s] at which to match with the input continuous- time system’s magnitude and phase (the gain=1 crossover frequency, for example). Should only be specified with method=’bilinear’ or ‘gbt’ with alpha=0.5 and ignored otherwise.
- Returns
sysd – Discrete time system, with sampling rate Ts
- Return type
Notes
Uses
scipy.signal.cont2discrete()
Examples
>>> sys = StateSpace(0, 1, 1, 0) >>> sysd = sys.sample(0.5, method='bilinear')
- slycot_laub(x)¶
Evaluate system’s transfer function at complex frequency using Laub’s method from Slycot.
Expects inputs and outputs to be formatted correctly. Use
sys(x)
for a more user-friendly interface.- Parameters
x (complex array_like or complex) – Complex frequency
- Returns
output – Frequency response
- Return type
(number_outputs, number_inputs, len(x)) complex ndarray
- property states¶
Deprecated attribute; use
nstates
instead.The
state
attribute was used to store the number of states for : a state space system. It is no longer used. If you need to access the number of states, usenstates
.
- zero()¶
Compute the zeros of a state space system.