Melanie Zeilinger: Katalogdaten im Frühjahrssemester 2021

NameFrau Prof. Dr. Melanie Zeilinger
LehrgebietIntelligente Regelsysteme
Adresse
Inst. Dynam. Syst. u. Regelungst.
ETH Zürich, ML L 13
Sonneggstrasse 3
8092 Zürich
SWITZERLAND
Telefon+41 44 632 53 45
E-Mailmzeilinger@ethz.ch
DepartementMaschinenbau und Verfahrenstechnik
BeziehungAusserordentliche Professorin

NummerTitelECTSUmfangDozierende
151-0073-31LARIS - Rocket Development Belegung eingeschränkt - Details anzeigen
Voraussetzung: Besuch der Lerneinheit 151-0073-30L ARIS - Rocket Development im HS20.
14 KP15AL. Guzzella, M. Zeilinger
KurzbeschreibungIm 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).
LernzielDie 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)
151-0660-00LModel Predictive Control Information 4 KP2V + 1UM. Zeilinger, A. Carron
KurzbeschreibungModel 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 and covers advanced topics.
LernzielDesign 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
- Nonlinear MPC: Theory and computation
- Hybrid MPC: Modeling hybrid systems and logic, mixed-integer optimization
- Simulation-based project providing practical experience with MPC
SkriptScript / lecture notes will be provided.
Voraussetzungen / BesonderesOne 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).
364-1058-00LRisk Center Seminar Series0 KP2SG. Sansavini, D. Basin, A. Bommier, D. N. Bresch, L.‑E. Cederman, P. Cheridito, H. Gersbach, F. Schweitzer, D. Sornette, B. Stojadinovic, B. Sudret, U. A. Weidmann, S. Wiemer, M. Zeilinger, R. Zenklusen
KurzbeschreibungThis course is a mixture between a seminar primarily for PhD and postdoc students and a colloquium involving invited speakers. It consists of presentations and subsequent discussions in the area of modeling and governing complex socio-economic systems, and managing risks and crises. Students and other guests are welcome.
LernzielParticipants should learn to get an overview of the state of the art in the field, to present it in a well understandable way to an interdisciplinary scientific audience, to develop novel mathematical models and approaches for open problems, to analyze them with computers or other means, and to defend their results in response to critical questions. In essence, participants should improve their scientific skills and learn to work scientifically on an internationally competitive level.
InhaltThis course is a mixture between a seminar primarily for PhD and postdoc students and a colloquium involving invited speakers. It consists of presentations and subsequent discussions in the area of modeling complex socio-economic systems and crises. For details of the program see the webpage of the seminar. Students and other guests are welcome.
SkriptThere is no script, but the sessions will be recorded and be made available. Transparencies of the presentations may be put on the course webpage.
LiteraturLiterature will be provided by the speakers in their respective presentations.
Voraussetzungen / BesonderesParticipants should have relatively good scientific, in particular mathematical skills and some experience of how scientific work is performed.