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
1 maintainer
Metadata
1 maintainer
Release files for control-toolbox 0.1.0
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