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.

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

!pip install control
import control as ct

• 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

• 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/

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.

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.

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 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

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.

Your contributions are welcome! Simply fork the GitHub repository and send a pull request.

Please see the Developer's Wiki for detailed instructions.