Melanie Zeilinger: Catalogue data in Autumn Semester 2020

Award: The Golden Owl
Name Prof. Dr. Melanie Zeilinger
FieldIntelligent Control Systems
Inst. Dynam. Syst. u. Regelungst.
ETH Zürich, LEE L 210
Leonhardstrasse 21
8092 Zürich
Telephone+41 44 632 53 45
DepartmentMechanical and Process Engineering
RelationshipAssociate Professor

151-0073-30LARIS - Rocket Development Restricted registration - show details
This course is part of a one-year course. The 14 credit points will be issued at the end of FS2021 with new enrolling for the same Focus Project in FS2021.

For MAVT BSc and ITET BSc only.

Prerequisites for the focus projects:
a. Basis examination successfully passed
b. Block 1 and 2 successfully passed

For enrollment, please contact the D-MAVT Student Administration.
0 credits15AL. Guzzella, M. Zeilinger
AbstractStudents develop and build a product from A-Z! They work in teams and independently, learn to structure problems, to identify solutions, system analysis and simulations, as well as presentation and documentation techniques. They build the product with access to a machine shop and state of the art engineering tools (Matlab, Simulink, etc).
ObjectiveThe various objectives of the Focus Project are:
- Synthesizing and deepening the theoretical knowledge from the basic courses of the 1. - 4. semester
- Team organization, work in teams, increase of interpersonal skills
- Independence, initiative, independent learning of new topic contents
- Problem structuring, solution identification in indistinct problem definitions, searches of information
- System description and simulation
- Presentation methods, writing of a document
- Ability to make decisions, implementation skills
- Workshop and industrial contacts
- Learning and recess of special knowledge
- Control of most modern engineering tools (Matlab, Simulink, CAD, CAE, PDM)
Prerequisites / NoticeThis Focus-Project is supervised by the following lecturers:
Siegwart, R., ASL
Haas, R., ASL
Beardsley P., Disney Research Zurich
151-0371-00LAdvanced Model Predictive Control Restricted registration - show details 4 credits2V + 1UM. Zeilinger, A. Carron, L. Hewing
AbstractModel predictive control (MPC) has established itself as a powerful control technique for complex systems under state and input constraints. This course discusses the theory and application of recent advanced MPC concepts, focusing on system uncertainties and safety, as well as data-driven formulations and learning-based control.
ObjectiveDesign, implement and analyze advanced MPC formulations for robust and stochastic uncertainty descriptions, in particular with data-driven formulations.
ContentTopics include
- Review of Bayesian statistics, stochastic systems and Stochastic Optimal Control
- Nominal MPC for uncertain systems (nominal robustness)
- Robust MPC
- Stochastic MPC
- Set-membership Identification and robust data-driven MPC
- Bayesian regression and stochastic data-driven MPC
- MPC as safety filter for reinforcement learning
Lecture notesLecture notes will be provided.
Prerequisites / NoticeBasic courses in control, advanced course in optimal control, basic MPC course (e.g. 151-0660-00L Model Predictive Control) strongly recommended.
Background in linear algebra and stochastic systems recommended.
364-1058-00LRisk Center Seminar Series0 credits2SB. Stojadinovic, D. Basin, A. Bommier, D. N. Bresch, L.‑E. Cederman, P. Cheridito, H. Gersbach, G. Sansavini, F. Schweitzer, D. Sornette, B. Sudret, S. Wiemer, M. Zeilinger, R. Zenklusen
AbstractThis 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. Students and other guests are welcome.
ObjectiveParticipants 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 for open problems, to analyze them with computers, 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.
ContentThis 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 colloquium. Students and other guests are welcome.
Lecture notesThere is no script, but a short protocol of the sessions will be sent to all participants who have participated in a particular session. Transparencies of the presentations may be put on the course webpage.
LiteratureLiterature will be provided by the speakers in their respective presentations.
Prerequisites / NoticeParticipants should have relatively good mathematical skills and some experience of how scientific work is performed.