Skip to content

README.md

Latest commit

 

History

History
21 lines (15 loc) · 1.01 KB

README.md

File metadata and controls

21 lines (15 loc) · 1.01 KB

Description

Model predictive control algorithms applied to various dynamic systems, developed in Python. Using the do-mpc and casadi package in Python. Systems implemented:

  • Spaceship
  • Kinematic bicycle model

Contents

  • models: Contains subfolders for each model. Model directory will have a description of the system, animated results and plots, and details for how to modify trajectories and tune parameters.
  • template: Contains template code to implement MPC on new systems with do-mpc package.
  • visualizer [WIP]: Folder containing Unity assets, resources, and scripts to visualize results from MPC control.

Dependencies

A conda environment running Python 3.x is recommended with the following packages

  • numpy
  • CasADi
  • matplotlib

The details for installing do-mpc can be found here: https://www.do-mpc.com/en/latest/installation.html

It is recommended to install the HSL MA27 solver for faster computation, which can be found here: http://www.hsl.rl.ac.uk/ipopt/