Melanie Zeilinger: Catalogue data in Spring Semester 2022 |  |
| 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 |
| mzeilinger@ethz.ch | |
| Department | Mechanical and Process Engineering |
| Relationship | Associate Professor |
| Number | Title | ECTS | Hours | Lecturers | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 151-0073-31L | Guidance, Navigation and Control for Recovery of a Sounding Rocket  Prerequisite: Enrollment for 151-0073-30L Guidance, Navigation and Control for Recovery of a Sounding Rocket in HS21. | 14 credits | 15A | 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 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 - 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). | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 173-0003-00L | Signals and Systems Only for MAS in Advanced Fundamentals of Mechatronics Engineering | 5 credits | 11G | M. Zeilinger, A. Carron | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | 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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Master the basics of signals and systems. Apply this knowledge to problems in the homework assignments and programming exercise. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Discrete-time signals and systems. Fourier- and z-Transforms. Frequency domain characterization of signals and systems. Time series analysis. Filter design. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | Lecture notes available on course website. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Competencies |
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| 364-1058-00L | Risk Center Seminar Series | 0 credits | 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 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | 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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | 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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | 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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | The sessions are recorded whenever possible and posted on the ETH Risk Center webpage. If available, presentation slides are shared as well. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | Each speaker will provide a literature review. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | In most cases, a quantitative background is required. Depending on the topic, field-specific knowledge may be required. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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