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Python Control System Toolbox

Project description

Python Control Systems Toolbox

Build Status Documentation Status PyPI version GitHub

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

Project details


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control-toolbox-0.1.0.tar.gz (13.3 kB view hashes)

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