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• Python Control Systems Library

MATLAB Compatibility Module — Python Control Systems Library 0.10.2 documentation

MATLAB compatibility subpackage.

This subpackage contains a number of functions that emulate some of the functionality of MATLAB. The intent of these functions is to provide a simple interface to the Python Control Systems Library (python-control) for people who are familiar with the MATLAB Control Systems Toolbox (tm).

Warning

This module is not closely maintained and some functionality in the main python-control package may not be be available via the MATLAB compatibility module.

tf(num, den[, dt])

Create a transfer function system.

ss(A, B, C, D[, dt])

Create a state space system.

frd(frdata, omega[, dt])

Construct a frequency response data (FRD) model.

zpk(zeros, poles, gain[, dt])

Create a transfer function from zeros, poles, gain.

mag2db(mag)

Convert a magnitude to decibels (dB).

db2mag(db)

Convert a gain in decibels (dB) to a magnitude.

c2d(sysc, Ts[, method, alpha, ...])

Convert a continuous-time system to discrete time by sampling.

ss2tf(sys)

Transform a state space system to a transfer function.

tf2ss(sys)

Transform a transfer function to a state space system.

tfdata(sys)

Return transfer function data objects for a system.

series(sys1, sys2[, ..., sysn])

Series connection of I/O systems.

parallel(sys1, sys2[, ..., sysn])

Parallel connection of I/O systems.

feedback(sys1[, sys2, sign])

Feedback interconnection between two I/O systems.

negate(sys, **kwargs)

Return the negative of a system.

connect(sys, Q, inputv, outputv)

Index-based interconnection of an LTI system.

append(sys1, sys2[, ..., sysn])

Group LTI models by appending their inputs and outputs.

dcgain(...)

Compute the gain of the system in steady state.

pole(sys)

Compute system poles.

zero(sys)

Compute system zeros.

damp(sys[, doprint])

Compute system's natural frequencies, damping ratios, and poles.

pzmap(sys[, grid, plot])

Plot a pole/zero map for a linear system.

step(sys[, T, input, output, return_x])

Step response of a linear system.

impulse(sys[, T, input, output, return_x])

Impulse response of a linear system.

initial(sys[, T, X0, input, output, return_x])

Initial condition response of a linear system.

lsim(sys[, U, T, X0])

Simulate the output of a linear system.

stepinfo(sysdata[, T, yfinal, ...])

Step response characteristics (rise time, settling time, etc).

bode(sys[, omega, dB, Hz, deg, ...])

Bode plot of the frequency response.

nyquist(syslist[, omega])

Nyquist plot of the frequency response.

margin(sys)     margin(mag, phase, omega)

Gain and phase margins and associated crossover frequencies.

nichols(data[, omega, grid, title, ax, label])

Nichols plot for a system.

ngrid()

Plot Nichols chart grid.

freqresp(sysdata[, omega, omega_limits, ...])

Frequency response of an LTI system.

evalfr(sys, x[, squeeze])

Evaluate transfer function of LTI system at complex frequency.

rlocus(sys[, gains, xlim, ylim, ...])

Root locus diagram.

sisotool(sys[, initial_gain, xlim_rlocus, ...])

Collection of plots inspired by MATLAB's sisotool.

place(A, B, p)

Place closed loop eigenvalues.

lqr(A, B, Q, R[, N])

Linear quadratic regulator design.

dlqr(A, B, Q, R[, N])

Discrete-time linear quadratic regulator design.

lqe(A, G, C, QN, RN, [, NN])

Continuous-time linear quadratic estimator (Kalman filter).

dlqe(A, G, C, QN, RN, [, N])

Discrete-time linear quadratic estimator (Kalman filter).

rss([states, outputs, inputs, strictly_proper])

Create a stable random state space object.

drss([states, outputs, inputs, strictly_proper])

Create a stable, discrete-time, random state space system.

ctrb(A, B[, t])

Controllability matrix.

obsv(A, C[, t])

Observability matrix.

gram(sys, type)

Gramian (controllability or observability).

minreal(sys[, tol, verbose])

Eliminate uncontrollable or unobservable states.

hsvd(sys)

Calculate the Hankel singular values.

balred(sys, orders[, method, alpha])

Balanced reduced order model of system of a given order.

modred(sys[, elim_states, method, ...])

Model reduction by input, output, or state elimination.

era(YY, r)

Calculate ERA model based on impulse-response data.

markov(Y, U, [, m])

Calculate Markov parameters [D CB CAB ...] from data.

pade(T[, n, numdeg])

Create a linear system that approximates a delay.

lyap(A, Q[, C, E, method])

Solves the continuous-time Lyapunov equation.

dlyap(A, Q[, C, E, method])

Solves the discrete-time Lyapunov equation.

care(A, B, Q[, R, S, E, stabilizing, ...])

Solves the continuous-time algebraic Riccati equation.

dare(A, B, Q, R[, S, E, stabilizing, ...])

Solves the discrete-time algebraic Riccati equation.

gangof4(response)     gangof4_plot(P, C, omega)

Plot response of "Gang of 4" transfer functions.

unwrap(angle[, period])

Unwrap a phase angle to give a continuous curve.

linspace(start, stop[, num, endpoint, ...])

Return evenly spaced numbers over a specified interval.

logspace(start, stop[, num, endpoint, base, ...])

Return numbers spaced evenly on a log scale.

ss2zpk(A, B, C, D[, input])

State-space representation to zero-pole-gain representation.

tf2zpk(b, a)

Return zero, pole, gain (z, p, k) representation from a numerator, denominator representation of a linear filter.

zpk2ss(z, p, k)

Zero-pole-gain representation to state-space representation

zpk2tf(z, p, k)

Return polynomial transfer function representation from zeros and poles

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