Schedule and Location

Monday, 10:00-11:30, Building 11, Room 262, Begin 22.10.2024

Lecturer

Prof. Dr.-Ing. Daniel Görges

Further Information

• Number of SWS: 2
• Number of ECTS Credits: 3
• Language: English
• Identifier: EIT-JEM-515-V-7
• Leistungspunkte: 3

Overview

Model predictive control belongs to the most important advanced control methods used in industrial practice. After manifold application in process systems, model predictive control has been increasingly utilized in mechatronic systems, vehicular systems, and power systems in recent years. Consequently, the demand for engineers who are familiar with model predictive control is high. In this lecture, thefundamentals of model predictive control  — e.g. prediction models, stability properties, reference tracking, and disturbance rejection — are introduced und illustrated by numerous examples using MATLAB/Simulink. Throughout the lecture, an active suspension system is studied as a practical example. Additionally, fundamentals of discrete-time systems, optimization, and robust control are explained. Finally, advanced model predictive control methods — particularly robust, explicit, hybrid, and distributed model predictive control — are presented. Furthermore, a workshop on implementing the most important methods under MATLAB will be done.

Content

1. Introduction to Model Predictive Control
2. Fundamentals of Discrete-Time Systems
3. Fundamentals of Optimization
4. Model Predictive Control without Constraints
5. Model Predictive Control with Constraints
6. Feasibility und Stability
7. Reference Tracking and Disturbance Rejection
8. Robust Model Predictive Control
9. Model Predictive Control with MATLAB

Preliminaries

Lineare Regelungen, Optimal Control (beneficial), CAE in der Regelungstechnik (beneficial)

Lecture Notes

The lecture notes will be provided in OLAT during the lecture. The password will be announced in the lecture

Exam

Informations to the exam will be provided in OLAT under Exam and Notifications.