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https://github.com/python-control/python-control

The Python Control Systems Library is a Python module that implements basic operations for analysis and design of feedback control systems.
https://github.com/python-control/python-control

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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.

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README 

        
.. image:: https://anaconda.org/conda-forge/control/badges/version.svg

   :target: https://anaconda.org/conda-forge/control



.. image:: https://img.shields.io/pypi/v/control.svg

   :target: https://pypi.org/project/control/



.. image:: https://github.com/python-control/python-control/actions/workflows/python-package-conda.yml/badge.svg

   :target: https://github.com/python-control/python-control/actions/workflows/python-package-conda.yml



.. image:: https://github.com/python-control/python-control/actions/workflows/install_examples.yml/badge.svg

   :target: https://github.com/python-control/python-control/actions/workflows/install_examples.yml



.. image:: https://github.com/python-control/python-control/actions/workflows/control-slycot-src.yml/badge.svg

   :target: https://github.com/python-control/python-control/actions/workflows/control-slycot-src.yml



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Python Control Systems Library

==============================



The Python Control Systems Library is a Python module that implements basic

operations for analysis and design of feedback control systems.



Have a go now!

--------------

Try out the examples in the examples folder using the binder service.



.. image:: https://mybinder.org/badge_logo.svg

 :target: https://mybinder.org/v2/gh/python-control/python-control/HEAD



The package can also be installed on Google Colab using the commands::



  !pip install control

  import control as ct



Features

--------



- Linear input/output systems in state-space and frequency domain

- Block diagram algebra: serial, parallel, feedback, and other interconnections

- Time response: initial, step, impulse

- Frequency response: Bode, Nyquist, and Nichols plots

- Control analysis: stability, reachability, observability, stability margins, root locus

- Control design: eigenvalue placement, linear quadratic regulator, sisotool, hinfsyn, rootlocus_pid_designer

- Estimator design: linear quadratic estimator (Kalman filter)

- Nonlinear systems: optimization-based control, describing functions, differential flatness



Links

-----



- Project home page: http://python-control.org

- Source code repository: https://github.com/python-control/python-control

- Documentation: http://python-control.readthedocs.org/

- Issue tracker: https://github.com/python-control/python-control/issues

- Mailing list: http://sourceforge.net/p/python-control/mailman/



Dependencies

------------



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



Installation

============



Conda and conda-forge

---------------------



The easiest way to get started with the Control Systems library is

using `Conda `_.



The Control Systems library has packages available using the `conda-forge

`_ 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.



Pip

---



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.



Installing from source

----------------------



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 .

  

Article and Citation Information

================================



An `article `_ 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



Development

===========



Code

----



You can check out the latest version of the source code with the command::



  git clone https://github.com/python-control/python-control.git



Testing

-------



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/



License

-------



This is free software released under the terms of `the BSD 3-Clause

License `_.  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.



Contributing

------------



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