Welcome to the materials for MECH 529 Advanced Mechanical Systems course at Colorado State University.
Course Overview¶
This course provides hands-on experience with advanced topics in mechanical systems control, including:
Python programming for control systems
Ordinary differential equations (ODEs)
Control system design and analysis
Linear Quadratic Regulator (LQR)
Trajectory tracking and generation
Model Predictive Control (MPC)
Reinforcement Learning (RL)
Laboratory Exercises¶
The course consists of 10 laboratory exercises and a final project:
Lab 1: Python Basics
Lab 2: ODEs
Lab 3: Introduction to Python Control
Lab 4: Closed Loop Control
Lab 5: LQR (Linear Quadratic Regulator)
Lab 6: Trajectory Tracking
Lab 7: Trajectory Generation
Lab 8: Model Predictive Control
Lab 9: Value Iteration & Policy Iteration
Lab 10: Reinforcement Learning
Final Project: Acrobot
Getting Started¶
Each lab is provided as a Jupyter notebook that you can download and run in your own environment. The notebooks contain both explanatory text and executable code cells.
Prerequisites¶
Basic knowledge of Python programming
Understanding of linear algebra and differential equations
Familiarity with control systems theory
Acknowledgements¶
Preparation of these lab materials was assisted by GitHub Copilot.
Some labs are adapted from or inspired by Jupyter notebooks created by Richard M. Murray at Caltech.
Colorado State University | Fall 2025