Advanced System and Control Theory
Advanced System and Control Theory

Themen sind die Analyse und Synthese der zeitdiskreten, Abtast- und Multiabtastsysteme sowie der vernetzten regelungstechnischen Systeme.
Im Rahmen dieser Vorlesung werden Standardmethoden für die Regelung und Beobachtung zeitdiskreter Systeme, Optimierungsverfahren vorgestellt. Ferner wird Modellierung von Multiabtastsysteme sowie der vernetzten regelungstechnischen Systeme behandelt.

Die Studierenden sollen Schemata zur Optimierung regelungstechnischer Systeme lernen und in der Lage sein, diese anzuwenden. Sie sollen ferne lernen, vernetzte regelungstechnische Systeme zu modellieren und analysieren.

[1] S. X. Ding, Vorlesungsskript "Advanced system and control theory" (wird jährlich aktualisiert, per Download verfügbar, will be updated and available for download)
[2] K. Zhou et al., Robust and Optimal Control, Prentice Hall, 1996.
[3] E.F. Camacho and C. Bordons, Model predictive control, Springer, 1999
[4] F.L. Lewis, D. Vrabie, L. Vassilis, Optimal Control (3rd Edition) John Wiley & Sons, 2012 

Essentials of control engineering

Höhere System- und Regelungstheorie

This course is devoted to the analysis and synthesis of discrete-time, sampled-data, multi-rate sampled data and networked control systems. It consists of four parts.
Part I: Introduction and basics. In this part, basic concepts for discrete control systems are reviewed, including state feedback controllers, observer-based state feedback controllers, stability check and decoupling controller design.
Part II: Optimal control schemes. In this part, four optimal control schemes are introduced:
- Model predictive control (MPC)
- linear quadratic regulator (LQR)
- Dynamic programming
- Calculus of variations and optimal control
Part III: Networked control systems. In this part, Multi-rate discrete-time systems, different types of networked control systems (NCS) are addressed. The focus is on the control-oriented modelling technique like lifting methods.
Part IV: LMI-aided system analysis and synthesis. In this part, design of H_2 and H_inf controllers for discrete-time systems with unknown inputs and model uncertainties is presented. To this end, LMI (linear matrix inequality) technique is applied.

The students should be able to model different types of networked control systems. Moreover, they should be able to apply optimal control schemes to real discrete-time systems.

[1] S. X. Ding, Vorlesungsskript "Advanced system and control theory" (wird jährlich aktualisiert, per Download verfügbar, will be updated and available for download)
[2] K. Zhou et al., Robust and Optimal Control, Prentice Hall, 1996.
[3] E.F. Camacho and C. Bordons, Model predictive control, Springer, 1999
[4] F.L. Lewis, D. Vrabie, L. Vassilis, Optimal Control (3rd Edition) John Wiley & Sons, 2012 

Essentials of control engineering