Automatic Control

Core Courses

First Year

Semester 1:

1. Analog Electronics I
2. Digital Systems I
3. Signal Processing
4. Electromagnetism and Waves
5. Electrical and Magnetic Circuits
6. Systems Theory
7. Continuous Linear Control Systems
8. Measurement Techniques
9. Numerical Methods Applied to Engineering Sciences
10. Scientific and Technical English 1
11. Written and Oral Communication 1
12. Discovery Internship 1

Semester 2:

1. Analog Electronics II
2. Digital Systems II
3. Electromagnetic Converters
4. Power Electronics
5. Sampled Control Systems
6. State-Space Analysis and Control
7. Programming Languages
8. Instrumentation
9. Scientific and Technical English 2
10. Written and Oral Communication 2
11. Renewable Energy and Sustainable Development
12. Internship 2

Advanced Topics

The Automatic Control covers advanced topics related to the control of dynamic systems, modeling, artificial intelligence applied to control, and the optimization of industrial processes. Below is a selection of the main topics covered in this field:

1. Advanced Control of Dynamic Systems

• Robust and Adaptive Control: H∞, sliding mode control, LQR/LQG, fuzzy control
• Model Predictive Control (MPC): real-time optimization
• Nonlinear Systems Control: feedback linearization, passivity-based control
• Fault-Tolerant Control: diagnosis and reconfiguration of control laws
• Distributed and Networked Control: multi-agent systems, synchronization

2. Modeling and System Identification

• Dynamic System Identification: parametric and non-parametric methods
• Hybrid and Event-Driven Systems: Petri nets, timed automata
• State Estimation and Observers: Kalman filters, particle filters
• Machine Learning for Modeling: neural networks, Bayesian regression

3. Artificial Intelligence and Automatic Control

• Deep Learning for Dynamic Systems Control
• Optimization Based on Genetic Algorithms, Particle Swarm Optimization (PSO), Ant Colony Optimization
• Adaptive Control through Reinforcement Learning (RL)
• Automatic Control and IoT: control of connected and intelligent systems

4. Automatic Control for Robotics and Autonomous Systems

• Control of Manipulator and Mobile Robots: visual servoing, SLAM, real-time control
• Drones and Autonomous Systems: trajectory control, robust navigation
• Human-Machine Interaction and Collaborative Control: exoskeletons, humanoid robots
• Embedded Systems for Real-Time Control: ROS, FPGA, real-time Linux

5. Cyber-Physical Systems and Industry 4.0

• Automation and Industrial Control Systems: SCADA, PLC, Industrial IoT
• Control of Energy Systems and Smart Grids
• Digital Twins and Simulation of Complex Systems
• Security and Cybersecurity in Automatic Control Systems

6. Dynamic Systems in Aerospace and Automotive Engineering

• Control of Drones and Aircraft: autopilot, trajectory optimization
• Advanced Driver Assistance Systems (ADAS): obstacle detection, sensor fusion
• Control and Supervision of Autonomous Vehicles: motion planning, SLAM

7. Optimization and Operational Research for Automatic Control

• Dynamic Optimization and Optimal Control: dynamic programming, variational methods
• Task Scheduling and Planning: graph theory, heuristic optimization
• Decision Support Systems and Multi-Criteria Decision-Making