Melanie Zeilinger: Katalogdaten im Frühjahrssemester 2022 |  |
| Name | Frau Prof. Dr. Melanie Zeilinger |
| Lehrgebiet | Intelligente Regelsysteme |
| Adresse | Inst. Dynam. Syst. u. Regelungst. ETH Zürich, LEE L 210 Leonhardstrasse 21 8092 Zürich SWITZERLAND |
| Telefon | +41 44 632 53 45 |
| mzeilinger@ethz.ch | |
| Departement | Maschinenbau und Verfahrenstechnik |
| Beziehung | Ausserordentliche Professorin |
| Nummer | Titel | ECTS | Umfang | Dozierende | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 151-0073-31L | Guidance, Navigation and Control for Recovery of a Sounding Rocket  Voraussetzung: Besuch der Lerneinheit 151-0073-30L Guidance, Navigation and Control for Recovery of a Sounding Rocket im HS21. | 14 KP | 15A | M. Zeilinger | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | Im Team ein Produkt von A-Z entwickeln und realisieren! Anwenden und Vertiefen des bestehenden Wissens, Arbeiten in Teams, Selbständigkeit, Problemstrukturierung, Lösungsfindung in unscharfen Problemstellungen, Systembeschreibung und -simulation, Präsentation und Dokumentation, Realisationsfähigkeit, Werkstatt- und Industriekontakte, Anwendung modernster Ingenieur-Werkzeuge (Matlab, Simulink usw). | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | Die vielfältigen Lernziele dieses Fokus-Projektes sind: - Synthetisieren und Vertiefen des theoretischen Wissens aus den Grundlagenfächern des 1.-4. Semesters - Teamorganisation, Arbeiten in Teams, Steigerung der sozialen Kompetenz - Selbständigkeit, Initiative, selbständiges Lernen neuer Themeninhalte - Problemstrukturierung, Lösungsfindung in unscharfen Problemstellungen, Suchen von Informationen - Systembeschreibung und -simulation - Präsentationstechnik, Dokumentationserstellung - Entscheidungsfähigkeit, Realisationsfähigkeit - Werkstatt- und Industriekontakte - Erweiterung und Vertiefung von Sachwissen - Beherrschung modernster Ingenieur-Werkzeuge (Matlab, Simulink, CAD, CAE, PDM) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 151-0660-00L | Model Predictive Control  | 4 KP | 2V + 1U | M. Zeilinger | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | Model predictive control is a flexible paradigm that defines the control law as an optimization problem, enabling the specification of time-domain objectives, high performance control of complex multivariable systems and the ability to explicitly enforce constraints on system behavior. This course provides an introduction to the theory and practice of MPC. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | Design and implement Model Predictive Controllers (MPC) for various system classes to provide high performance controllers with desired properties (stability, tracking, robustness,..) for constrained systems. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | - Review of required optimal control theory - Basics on optimization - Receding-horizon control (MPC) for constrained linear systems - Theoretical properties of MPC: Constraint satisfaction and stability - Computation: Explicit and online MPC - Practical issues: Tracking and offset-free control of constrained systems, soft constraints - Robust MPC: Robust constraint satisfaction - Simulation-based project providing practical experience with MPC | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Skript | Script / lecture notes will be provided. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | One semester course on automatic control, Matlab, linear algebra. Courses on signals and systems and system modeling are recommended. Important concepts to start the course: State-space modeling, basic concepts of stability, linear quadratic regulation / unconstrained optimal control. Expected student activities: Participation in lectures, exercises and course project; homework (~2hrs/week). | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 173-0003-00L | Signals and Systems Only for MAS in Advanced Fundamentals of Mechatronics Engineering | 5 KP | 11G | M. Zeilinger, A. Carron | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | Signals arise in most engineering applications. They contain information about the behavior of physical systems. Systems respond to signals and produce other signals. In this course, we explore how signals can be represented and manipulated, and their effects on systems. We further explore how we can discover basic system properties by exciting a system with various types of signals. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | Master the basics of signals and systems. Apply this knowledge to problems in the homework assignments and programming exercise. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | Discrete-time signals and systems. Fourier- and z-Transforms. Frequency domain characterization of signals and systems. Time series analysis. Filter design. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Skript | Lecture notes available on course website. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kompetenzen |
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| 364-1058-00L | Risk Center Seminar Series | 0 KP | 2S | H. Schernberg, D. Basin, A. Bommier, D. N. Bresch, S. Brusoni, L.‑E. Cederman, P. Cheridito, F. Corman, H. Gersbach, C. Hölscher, K. Paterson, G. Sansavini, D. Sornette, B. Stojadinovic, B. Sudret, J. Teichmann, R. Wattenhofer, U. A. Weidmann, S. Wiemer, M. Zeilinger, R. Zenklusen | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kurzbeschreibung | In this series of seminars, invited speakers discuss various topics in the area of risk modelling, governance of complex socio-economic systems, managing risks and crises, and building resilience. Students, PhD students, post-docs, faculty and individuals outside ETH are welcome. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lernziel | Participants gain insights in a broad range of risk- and resilience-related topics. They expand their knowledge of the field and deepen their understanding of the complexity of our social, economic and engineered systems. For young researchers in particular, the seminars offer an opportunity to learn academic presentation skills and to network with an interdisciplinary scientific audience. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Inhalt | Academic presentations from ETH faculty as well as external researchers. Each seminar is followed by a Q&A session and (when permitted) a networking Apéro. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Skript | The sessions are recorded whenever possible and posted on the ETH Risk Center webpage. If available, presentation slides are shared as well. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literatur | Each speaker will provide a literature review. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Voraussetzungen / Besonderes | In most cases, a quantitative background is required. Depending on the topic, field-specific knowledge may be required. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Kompetenzen |
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