Difference between revisions of "Control Systems Library for Python"

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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.
{{warning|The information on this page is out of date.  The most up-to-date information about python-control is available in the documentation that is distributed with the package.


== Architecture notes ==
'''[http://sourceforge.net/p/python-control/wiki/Home/ python-control home on SourceForge]'''


== Installation instructions ==
}}


I'm using the [http://ipython.scipy.org/moin/ IPython] environment, with the the [http://matplotlib.sourceforge.net/ matplotlib] extensions (which enables MATLAB-like plotting).  I am doing all of my playing on OS X, using fink.
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<font color='blue' size='+2'>Python Control Systems Library (python-control)</font></td></tr>
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Here's what I had to do to get the basic setup that I am using.
<br>
# Install SciPy - I did this using fink. Have to use the main/unstable tree.
{| style="float: right" width=30% border=1
# Install matplotlib - Need this for plotting
|-
# Install ipython - interactive python interface
|
==== Announcements ====
* The python-control user documentation has been shifted from SourceForge to MurrayWiki at Caltech.  Developer documentation remains on [http://python-control.sf.net SourceForge].
* Version 0.5a has been released: [http://sourceforge.net/mailarchive/message.php?msg_id=27912588 release notes], [http://sourceforge.net/projects/python-control/files/ file download]
|}
The Python Control Systems Library, python-control, is a python package that implements basic operations for analysis and design of feedback control systems.
* [http://python-control.sourceforge.net/manual User manual] - Sphinx documentation for the python-control package
* [[http:sourceforge.net/p/python-control/wiki/Download/|Download]] - download and install the latest release of the package
* [[python-control/Example: Vertical takeoff and landing aircraft|Example: Vertical takeoff and landing aircraft]] - demonstration of package capabilities
* [https://lists.sourceforge.net/lists/listinfo/python-control-announce Announcements mailing list] - sign up to receive announcements about python-control
<!-- * [[http:sourceforge.net/p/python-control/wiki/Developer%20information/|Developer information]] -  project information for active python-control developers -->
* [https://sourceforge.net/projects/python-control/ Project description page] - summary of all project information (SourceForge)


Small snipped of code for testing if everything is installed
=== Project Overview ===
import from scipy *
import from matlibplot *
a = zeros(1000)
a[:100]=1
b = fft(a)
plot(abs(b))
show()


== Related documentation ==
The python-control package is a set of python classes and functions that implement common operations for the analysis and design of feedback control systems.  The initial goal is to implement all of the functionality required to work through the examples in the textbook ''[http://www.cds.caltech.edu/~murray/amwiki Feedback Systems]'' by &Aring;str&ouml;m and Murray.  A MATLAB compatibility package (control.matlab) is available that provides functions corresponding to the commands available in the MATLAB Control Systems Toolbox.


=== Python documentation ===
Here are some of the basic functions that are (or will be) available in the package:
* [http://www.scipy.org/ SciPy.org] - main web site for SciPy
* Linear input/output systems in state space and frequency domain (transfer functions)
** [http://ipython.scipy.org/moin/ IPython] - enhanced shell for python
* Block diagram algebra: serial, parallel and feedback interconnections
** [http://matplotlib.sourceforge.net/ matplotlib] - 2D plotting for python
* Time response: initial, step, impulse (using the scipy.signal package)
* Frequency response: Bode and Nyquist plots
* Control analysis: stability, reachability, observability, stability margins
* Control design: eigenvalue placement, linear quadratic regulator
* Estimator design: linear quadratic estimator (Kalman filter)

Latest revision as of 21:11, 31 May 2015

WARNING: The information on this page is out of date. The most up-to-date information about python-control is available in the documentation that is distributed with the package.

python-control home on SourceForge

Python Control Systems Library (python-control)


Announcements

  • The python-control user documentation has been shifted from SourceForge to MurrayWiki at Caltech. Developer documentation remains on SourceForge.
  • Version 0.5a has been released: release notes, file download

The Python Control Systems Library, python-control, is a python package that implements basic operations for analysis and design of feedback control systems.

Project Overview

The python-control package is a set of python classes and functions that implement common operations for the analysis and design of feedback control systems. The initial goal is to implement all of the functionality required to work through the examples in the textbook Feedback Systems by Åström and Murray. A MATLAB compatibility package (control.matlab) is available that provides functions corresponding to the commands available in the MATLAB Control Systems Toolbox.

Here are some of the basic functions that are (or will be) available in the package:

  • Linear input/output systems in state space and frequency domain (transfer functions)
  • Block diagram algebra: serial, parallel and feedback interconnections
  • Time response: initial, step, impulse (using the scipy.signal package)
  • Frequency response: Bode and Nyquist plots
  • Control analysis: stability, reachability, observability, stability margins
  • Control design: eigenvalue placement, linear quadratic regulator
  • Estimator design: linear quadratic estimator (Kalman filter)