PyAdvancedControl

by AtsushiSakai

AtsushiSakai / PyAdvancedControl

Python codes for advanced control

235 Stars 117 Forks Last release: Not found MIT License 121 Commits 0 Releases

Available items

No Items, yet!

The developer of this repository has not created any items for sale yet. Need a bug fixed? Help with integration? A different license? Create a request here:

PyAdvancedControl

Build Status

Python Codes for Advanced Control

Dependencies

  • Python 3.7.x

  • cvxpy 1.0.x

  • ecos 2.0.7

  • cvxopt 1.2.x

  • scipy 1.1.0

  • numpy 1.15.0

  • matplotlib 2.2.2

lqr_sample

This is a sample code of Linear-Quadratic Regulator

This is LQR regulator simulation.

1

This is LQR tracking simulation.

1

finitehorizonoptimal_control

This is a finite horizon optimal control sample code

1

mpc_sample

This is a sample code of a simple Model Predictive Control (MPC) regulator simulation

1

mpc_tracking

This is a sample code of a Model Predictive Control (MPC) traget tracking simulation

1

mpc_modeling

This is a sample code for model predictive control optimization modeling without any modeling tool (e.g cvxpy)

This means it only use a solver (cvxopt) for MPC optimization.

It includes two MPC optimization functions:

1 optmpcwithinputconst()

It can be applied input constraints (not state constraints).

2 optmpcwithstateconst()

It can be applied state constraints and input constraints.

This figure is a comparison of MPC results with and without modeling tool.

1

invertedpendulummpc_control

1

This is a inverted pendulum mpc control simulation.

tools

c2d

This is a API compatible function of MATLAB c2d function.

Convert model from continuous to discrete time MATLAB c2d

We use cookies. If you continue to browse the site, you agree to the use of cookies. For more information on our use of cookies please see our Privacy Policy.