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Control Systems Lab

Minimal experiments illustrating feedback control and system dynamics in control systems.

This repository explores simple simulations of control system behaviour commonly encountered in robotics, automation, and cyber-physical systems.

The examples demonstrate how feedback control mechanisms can regulate system behaviour and maintain stability in dynamic environments.

Contents

The src/ directory contains three minimal experiments:

• pid_controller_sim.py

  Implements a simple proportional–integral–derivative (PID) controller regulating a simulated system.

• system_response_sim.py

  Demonstrates the step response of a simple dynamic system.

• feedback_control_demo.py

  Simulates closed-loop feedback control regulating a system toward a target value.

Purpose

These experiments illustrate engineering concepts relevant to:

• control systems engineering
• feedback control
• robotics control architectures
• cyber-physical systems

Motivation

Control systems are fundamental to robotics, automation, and mechatronic systems.

Most real-world machines rely on feedback control mechanisms to regulate motion, maintain stability, and respond to disturbances.

Understanding how dynamic systems behave under feedback control is essential for designing reliable cyber-physical systems.

Method

The repository implements simplified simulations of control system behaviour.

The experiments include:

• PID control for regulating system output
• dynamic system response to step inputs
• closed-loop feedback control

These implementations are intentionally minimal and focus on illustrating the conceptual behaviour of feedback control systems rather than full industrial control implementations.

Running the examples

Clone the repository and run any of the scripts:

git clone https://github.com/Jorge-de-la-Flor/control-systems-lab
cd control-systems-lab
python src/pid_controller_sim.py

Each script simulates system behaviour and prints the resulting control process in the console.

Example output

Project tree

control-systems-lab
├─ .python-version
├─ LICENSE
├─ README.es.md
├─ README.md
├─ assets
│  ├─ feedback_control.png
│  ├─ pid_controller.png
│  └─ step_response_simulation.png
├─ pyproject.toml
├─ src
│  ├─ feedback_control_demo.py
│  ├─ pid_controller_sim.py
│  └─ system_response_sim.py
└─ uv.lock

Requirements

The examples use:

• Python 3.12+
• NumPy
• Matplotlib

Installation

Install the required dependencies:

• using pip

pip install numpy matplotlib

• using uv

uv add numpy matplotlib

References

• Åström, K. J., & Murray, R. M. (2008). Feedback Systems.

• Ogata, K. (2010). Modern Control Engineering.