Control Engineering with Python

Notations

📚 Program & Slides

0. Introduction to Control Engineering (HTML, PDF, IPYNB)

1. Introduction to Dynamical Systems

   • Models (HTML, PDF, IPYNB)

   • Simulation (HTML, PDF, IPYNB)

   • Well-posedness (HTML, PDF, IPYNB)

   • Asymptotic Behavior (HTML, PDF, IPYNB)

2. Linear-Time Invariant Systems

   • LTI Models (HTML, PDF, IPYNB)

   • Internal dynamics (HTML, PDF, IPYNB)

   • I/O behavior (HTML, PDF, IPYNB)

3. Controller Design

   • Controllability (HTML, PDF, IPYNB)

   • Asymptotic Stabilization (HTML, PDF, IPYNB)

   • Optimal Control (HTML, PDF, IPYNB)

4. Observers (HTML, PDF, IPYNB)

   • Observability

   • Observer design: pole assignment & optimal filtering

5. Application to mobile robotics

   • Lagrangian mechanics

   • Kinematic models of mobile robots

   • Control of mobile robots

📓 Notebooks

The course contents are also available as Jupyter notebooks. Open, edit and run these notebooks either

• ☁️ in the cloud: open project with Binder or

• 💻 on your computer: follow the instructions.

🚀 Project

• :octocat: Fork this project as a starting point;
  when needed, "fetch upstream" to get the project updates.

🎉 Extra resources

💻 Animation of dynamical systems

Example notebook: double pendulum

• view in GitHub,

• open in binder.

📚 Free External Resources

• 📖 Nicolas Rougier – Scientific Visualization: Python + Matplotlib

• 📖 Eduardo Sontag – Mathematical Control Theory

• 📖 Vladimír Kučera – Riccati Equations and their Solution

• 📖 The Zodiac – Theory of Robot Control

This work is licensed under a Creative Commons Attribution 4.0 International License.