Control Systems Library for Python

From Murray Wiki
Jump to navigationJump to search

This page collects some notes on a control systems library for Python. The plan is to create an alternative to the MATLAB Control System Toolbox™ that can be used in courses and for research. This page collects information about the toolbox, in preparation for actually writing some code. If you stumble across this page and know of a similar package or would like to contribute, let me know.

Status updates:

  • 23 May 09: really basic functionality working (Bode and Nyquist plots of transfer functions)
  • 24 May 09: looking around for open source control computations - slicot looks like a candidate

Architecture notes

I'm trying to sort out the best object structure to use for control system objects. There is already an LTI class in the signal processing module of SciPY, so I might be able to build on that (and hence get those systems for free). Ideally, I'd like to allow for time delay in the linear systems representation, since these come up a lot in my group's research.

Here's some rough thoughts on a possible object structure:

  • InputOutputSystem - dynamical system with inputs and outputs. Could be linear or nonlinear, discrete or continuous time (?), include infinite dimensional systems (time-delays, perhaps some classes of PDEs?). Should be compatible, if possible, with the ODE integrators that are part of SciPy (so that I can use that for simulating systems).
    • StateSpaceSystem - state space representation of an input/output system
      • LinearStateSpaceSystem - linear system in state space form (ideally with time-delays)
    • TransferFunction - frequency domain representation of an input/output system

Installation instructions

I'm using the IPython environment, with SciPy extensions for scientific computing plus the matplotlib extensions (which enables MATLAB-like plotting). I am doing all of my playing on OS X, using fink.

Here's what I had to do to get the basic setup that I am using.

  1. Install SciPy - I did this using fink. Have to use the main/unstable tree.
  2. Install matplotlib - Need this for plotting
  3. Install ipython - interactive python interface

Small snipped of code for testing if everything is installed

import from scipy *
import from matlibplot *
a = zeros(1000)
b = fft(a)

Related documentation

Python documentation

  • - main web site for SciPy
  • PyRo - Python Robotics library (might be nice to be compatible with this

Related packages

  • SLICOT - Fortran 77 implementations of numerical algorithms for computations in systems and control theory
    • python wrapper - Numpy wrapper of the control and systems library SLICOT
  • Octave Control Systems Toolbox - documentation for the Octave implementation (not sure what code is used for computing results)