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: