Python Control Systems Library
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The Python Control Systems Library is a Python module that implements basic operations for analysis and design of feedback control systems.
Try out the examples in the examples folder using the binder service.
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The package can also be installed on Google Colab using the commands::
!pip install control import control as ct
The package requires numpy, scipy, and matplotlib. In addition, some routines use a module called slycot, that is a Python wrapper around some FORTRAN routines. Many parts of python-control will work without slycot, but some functionality is limited or absent, and installation of slycot is recommended (see below). The Slycot wrapper can be found at:
https://github.com/python-control/Slycot
The easiest way to get started with the Control Systems library is
using Conda <https://conda.io>
_.
The Control Systems library has packages available using the conda-forge <https://conda-forge.org>
_ Conda channel, and as of Slycot version
0.3.4, binaries for that package are available for 64-bit Windows,
OSX, and Linux.
To install both the Control Systems library and Slycot in an existing conda environment, run::
conda install -c conda-forge control slycot
Mixing packages from conda-forge and the default conda channel can sometimes cause problems with dependencies, so it is usually best to instally NumPy, SciPy, and Matplotlib from conda-forge as well.
To install using pip::
pip install slycot # optional; see below pip install control
If you install Slycot using pip you'll need a development environment (e.g., Python development files, C and Fortran compilers). Pip installation can be particularly complicated for Windows.
To install from source, get the source code of the desired branch or release
from the github repository or archive, unpack, and run from within the
toplevel python-control
directory::
pip install .
An article <https://ieeexplore.ieee.org/abstract/document/9683368>
_ about
the library is available on IEEE Explore. If the Python Control Systems Library helped you in your research, please cite::
@inproceedings{python-control2021, title={The Python Control Systems Library (python-control)}, author={Fuller, Sawyer and Greiner, Ben and Moore, Jason and Murray, Richard and van Paassen, Ren{'e} and Yorke, Rory}, booktitle={60th IEEE Conference on Decision and Control (CDC)}, pages={4875--4881}, year={2021}, organization={IEEE} }
or the GitHub site: https://github.com/python-control/python-control
You can check out the latest version of the source code with the command::
git clone https://github.com/python-control/python-control.git
You can run the unit tests with pytest
_ to make sure that everything is
working correctly. Inside the source directory, run::
pytest -v
or to test the installed package::
pytest --pyargs control -v
.. _pytest: https://docs.pytest.org/
This is free software released under the terms of the BSD 3-Clause License <http://opensource.org/licenses/BSD-3-Clause>
_. There is no
warranty; not even for merchantability or fitness for a particular
purpose. Consult LICENSE for copying conditions.
When code is modified or re-distributed, the LICENSE file should accompany the code or any subset of it, however small. As an alternative, the LICENSE text can be copied within files, if so desired.
Your contributions are welcome! Simply fork the GitHub repository and send a
pull request
_.
.. _pull request: https://github.com/python-control/python-control/pulls
Please see the Developer's Wiki
_ for detailed instructions.
.. _Developer's Wiki: https://github.com/python-control/python-control/wiki