Control Engineering with Python

Notations

:books: 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

:notebook: Notebooks

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

• :cloud: in the cloud: open project with Binder or

• :computer: on your computer: follow the instructions.

:rocket: Project

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

:tada: Extra resources

:computer: Animation of dynamical systems

Example notebook: double pendulum

• view in GitHub,

• open in binder.

:books: Free External Resources

• :book: Nicolas Rougier – Scientific Visualization: Python + Matplotlib

• :book: Eduardo Sontag – Mathematical Control Theory

• :book: Vladimír Kučera – Riccati Equations and their Solution

• :book: The Zodiac – Theory of Robot Control

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