inf341 - Robust Control and State Estimation in Digitalised Energy Systems (Course overview) - Campusmanagementsystem Stud.IP

inf341 - Robust Control and State Estimation in Digitalised Energy Systems (Course overview)

Department of Computing Science

6 KP

Module components

Semester courses Wintersemester 2022/2023

Examination

Lecture

2.01.341 - Robust Control and State Estimation
- Prof. Dr.-Ing. habil. Andreas Rauh
- Marit Lahme
- Oussama Benzinane
Tuesday: 14:15 - 15:45, weekly (from 18/10/22), V
Tuesday: 16:15 - 17:45, weekly (from 18/10/22), Ü
Dates on Thursday, 24.11.2022 16:00 - 20:00, Friday, 10.02.2023 10:00 - 12:00, Thursday, 16.02.2023 14:00 - 15:00, Thursday, 16.02.2023 14:00 - 16:00
1. Robustness of linear systems/ system analysis • Boundary crossing theorem of Frazer and Duncan • Mikhailov criterion • Kharitonov criterion • Frequency response approaches 2. Selected control design techniques/ control synthesis • Parameter-space approach of Ackermann and Kaesbauer • Eigenvalue and eigenvalue domain assignment • H-infinity control • Frequency response approaches (Sensitivity function approaches in the frequency domain) 3. Robust LMI-based control techniques • Lyapunov stability • Polytopic uncertainty modeling • Optimality of solutions 4. Duality between control and observer synthesis • Robust state estimation • Sliding mode observers 5. Interval methods: Solution of static and dynamic problems (Enclosing function values, Branch-and-bound techniques, Verification techniques for differential equations) 6. Fundamentals: Fault detection and fault-tolerant control

Exercises

2.01.341 - Robust Control and State Estimation
- Prof. Dr.-Ing. habil. Andreas Rauh
- Marit Lahme
- Oussama Benzinane
Tuesday: 14:15 - 15:45, weekly (from 18/10/22), V
Tuesday: 16:15 - 17:45, weekly (from 18/10/22), Ü
Dates on Thursday, 24.11.2022 16:00 - 20:00, Friday, 10.02.2023 10:00 - 12:00, Thursday, 16.02.2023 14:00 - 15:00, Thursday, 16.02.2023 14:00 - 16:00
1. Robustness of linear systems/ system analysis • Boundary crossing theorem of Frazer and Duncan • Mikhailov criterion • Kharitonov criterion • Frequency response approaches 2. Selected control design techniques/ control synthesis • Parameter-space approach of Ackermann and Kaesbauer • Eigenvalue and eigenvalue domain assignment • H-infinity control • Frequency response approaches (Sensitivity function approaches in the frequency domain) 3. Robust LMI-based control techniques • Lyapunov stability • Polytopic uncertainty modeling • Optimality of solutions 4. Duality between control and observer synthesis • Robust state estimation • Sliding mode observers 5. Interval methods: Solution of static and dynamic problems (Enclosing function values, Branch-and-bound techniques, Verification techniques for differential equations) 6. Fundamentals: Fault detection and fault-tolerant control

Hinweise zum Modul

Prerequisites	Basic knowledge of the control of linear continuous-time and/or discrete-time systems or of robust control
Prüfungszeiten	Written exam: at the end of the lecture period Portfolio: during the semester
Module examination	Portfolio or written exam
Skills to be acquired in this module	The students identify fundamentals of robust control and state estimation as well as problem-specific solution techniques and their corresponding software implementation. Professional competences The students identify fundamentals of robust control and state estimation characterize problem-specific solution techniques for different classes of uncertainty are aware of reliable software implementations. Methological competences The students analyze problems of robust control and state estimation for dynamic systems analyze fundamental solution techniques on a theoretical basis transfer as well as generalize those independently to new fields of applications. Social competences The students develop solution ideas for real-life control problems within an accompanying project in small teams explain the obtained results in short presentations. Self competences The students critically reflect the achieved results of their project work acknowledge limitations of various approaches for robust control and state estimation.