Python Control Systems ToolboxΒΆ
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.
Documentation: