Python Control Systems Toolbox

The control-toolbox is a Python Library for implementing and simulating various systems and control strategies.

Current Supported Functionality:

• System modeling with Transfer Functions and State Space Representations.
• Time Domain Response.
• Frequency Response.
• System Representation conversion: State Space model to Transfer Function and vice versa.
• Block diagram algebra: Series and Parallel.
• Stability Analysis.
• Root Locus.
• Bode Plot.
• Parameterization of System.
• Pole-Zero / Eigenvalue plot of systems.
• Feedback analysis.
• PID control.
• Observability and Controllability.
• Full State Feedback.
• Full State Observer.
• Linear Quadratic Regulator(LQR).
• Linear Quadratic Estimator(LQE) / Kalman Filter.
• Linearization.
• System Identification.

Future Updates:

• Linear Quadratic Gaussian Control.
• Extended Kalman Filter.
• Unscented Kalman filter.
• Model Predictive Control.

Project Links

Project Homepage: http://control-toolbox.rtfd.io/
Documentation: https://control-toolbox.readthedocs.io/

Installation

Pip

To install using pip, run the following command:

pip install control-toolbox

Development

To get the latest unreleased version:

git clone https://github.com/rushad7/control-toolbox.git