Suchergebnis: Katalogdaten im Herbstsemester 2019
Elektrotechnik und Informationstechnologie Master  | ||||||
 Master-Studium (Studienreglement 2008) | ||||||
| Fächer der Vertiefung Insgesamt 42 KP müssen im Masterstudium aus Vertiefungsfächern erreicht werden. Der individuelle Studienplan unterliegt der Zustimmung eines Tutors. | ||||||
| Systems and Control | ||||||
| Kernfächer Diese Fächer sind besonders empfohlen, um sich in "Systems and Control" zu vertiefen. | ||||||
| Nummer | Titel | Typ | ECTS | Umfang | Dozierende | |
|---|---|---|---|---|---|---|
| 227-0225-00L | Linear System Theory | W | 6 KP | 5G | J. Lygeros | |
| Kurzbeschreibung | The class is intended to provide a comprehensive overview of the theory of linear dynamical systems, stability analysis, and their use in control and estimation. The focus is on the mathematics behind the physical properties of these systems and on understanding and constructing proofs of properties of linear control systems. | |||||
| Lernziel | Students should be able to apply the fundamental results in linear system theory to analyze and control linear dynamical systems. | |||||
| Inhalt | - Proof techniques and practices. - Linear spaces, normed linear spaces and Hilbert spaces. - Ordinary differential equations, existence and uniqueness of solutions. - Continuous and discrete-time, time-varying linear systems. Time domain solutions. Time invariant systems treated as a special case. - Controllability and observability, duality. Time invariant systems treated as a special case. - Stability and stabilization, observers, state and output feedback, separation principle. | |||||
| Skript | Available on the course Moodle platform. | |||||
| Voraussetzungen / Besonderes | Sufficient mathematical maturity, in particular in linear algebra, analysis. | |||||
| 227-0697-00L | Industrial Process Control | W | 4 KP | 3G | A. Horch, M. Mercangöz | |
| Kurzbeschreibung | Introduction to industrial automation systems with application to the process industry, power generation as well as discrete manufacturing. | |||||
| Lernziel | General understanding of industrial automation systems in different industries. Purpose, architecture, technologies, application examples, current and future trends. | |||||
| Inhalt | Introduction to process automation: system architecture, data handling, communication (fieldbuses), process visualization, and engineering. Differences and characteristics of discrete and process industries. Analysis and design of open loop control problems: discrete automata, finite state machines, decision tables, and petri-nets. Practical analysis and design of closed-loop control for the process industry. Automation Engineering: Application programming in IEC 61131-3 (ladder diagrams, function blocks, sequence control, structured text); PLC programming and simulation, process visualization and operation; engineering integration from sensors, cabling, topology design, function, visualization, diagnosis, to documentation; Industry standards (e.g. OPC, Profibus); Ergonomic design, safety (IEC61508) and availability, supervision and diagnosis. Automation standards: Communication, Architecture, Engineering, dependable systems, functional safety, automation security. Extensive practical examples from different process industries, power generation, gas compressor control, and automotive manufacturing. | |||||
| Skript | Slides will be available as .PDF documents, see "Learning materials" (for registered students only) | |||||
| Literatur | References will be given at the end of individual lectures. | |||||
| Voraussetzungen / Besonderes | Exercises: Tuesday 15-16 Practical exercises will illustrate some topics, e.g. some control software coding using industry standard programming tools based on IEC61131-3. | |||||
| 151-0563-01L | Dynamic Programming and Optimal Control | W | 4 KP | 2V + 1U | R. D'Andrea | |
| Kurzbeschreibung | Introduction to Dynamic Programming and Optimal Control. | |||||
| Lernziel | Covers the fundamental concepts of Dynamic Programming & Optimal Control. | |||||
| Inhalt | Dynamic Programming Algorithm; Deterministic Systems and Shortest Path Problems; Infinite Horizon Problems, Bellman Equation; Deterministic Continuous-Time Optimal Control. | |||||
| Literatur | Dynamic Programming and Optimal Control by Dimitri P. Bertsekas, Vol. I, 3rd edition, 2005, 558 pages, hardcover. | |||||
| Voraussetzungen / Besonderes | Requirements: Knowledge of advanced calculus, introductory probability theory, and matrix-vector algebra. | |||||
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