Melanie Zeilinger: Catalogue data in Spring Semester 2021

Name	Prof. Dr. Melanie Zeilinger
Field	Intelligent Control Systems
Address	Inst. Dynam. Syst. u. Regelungst. ETH Zürich, LEE L 210 Leonhardstrasse 21 8092 Zürich SWITZERLAND
Telephone	+41 44 632 53 45
E-mail	mzeilinger@ethz.ch
Department	Mechanical and Process Engineering
Relationship	Associate Professor

Number	Title	ECTS	Hours	Lecturers
151-0073-31L	ARIS - Rocket Development Prerequisite: Enrollment for 151-0073-30L ARIS - Rocket Development in HS20.	14 credits	15A	L. Guzzella, M. Zeilinger
Abstract	Students 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).
Learning objective	The 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)
151-0660-00L	Model Predictive Control	4 credits	2V + 1U	M. Zeilinger, A. Carron
Abstract	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 and covers advanced topics.
Learning objective	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.
Content	- 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
Lecture notes	Script / lecture notes will be provided.
Prerequisites / Notice	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).
364-1058-00L	Risk Center Seminar Series	0 credits	2S	G. 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
Abstract	This 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.
Learning objective	Participants 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.
Content	This 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.
Lecture notes	There is no script, but the sessions will be recorded and be made available. Transparencies of the presentations may be put on the course webpage.
Literature	Literature will be provided by the speakers in their respective presentations.
Prerequisites / Notice	Participants should have relatively good scientific, in particular mathematical skills and some experience of how scientific work is performed.