Python Control Systems Library

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

Features

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

• Nonlinear input/output system modeling, simulation, and analysis

• Block diagram algebra: serial, parallel, and feedback interconnections

• Time response: initial, step, impulse, and forced response

• Frequency response: Bode, Nyquist, and Nichols plots

• Control analysis: stability, reachability, observability, stability margins, phase plane plots, root locus plots

• Control design: eigenvalue placement, LQR, H2, Hinf, and MPC/RHC

• Trajectory generation: optimal control and differential flatness

• Model reduction: balanced realizations and Hankel singular values

• Estimator design: linear quadratic estimator (Kalman filter), MLE, and MHE

Links:

• GitHub repository: https://github.com/python-control/python-control

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

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

How to cite

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.

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

pytest -v

pytest --pyargs control -v