This repository contains a collection of Jupyter Notebook examples that demonstrate fundamental control system techniques using Python. It is designed for students, educators, and enthusiasts looking to explore and understand classic and modern control strategies through interactive simulations and visualizations. Each notebook is self-contained and focuses on a specific control technique.

The up to date theory is on the Wiki of the repository. The Control_Theory__The_Basics.pdf is not maintained.

• Python 3.x
• Jupyter Notebook
• numpy, scipy, matplotlib — core scientific stack
• control — Python control systems library
• cvxpy — used for MPC and optimization-based examples

Clone the repo:

git clone https://github.com/guidosassaroli/controlbasics

This project is ideal for:

• Control systems students learning through simulation
• Professors and TAs creating examples or assignments
• Engineers brushing up on core control theory concepts
• Anyone curious about how systems like cruise control, thermostats, or drones work under the hood