Suchergebnis: Katalogdaten im Frühjahrssemester 2018

Robotics, Systems and Control Master Information
Kernfächer
NummerTitelTypECTSUmfangDozierende
151-0116-10LHigh Performance Computing for Science and Engineering (HPCSE) for Engineers II Information W4 KP4GP. Koumoutsakos, P. Chatzidoukas
KurzbeschreibungThis course focuses on programming methods and tools for parallel computing on multi and many-core architectures. Emphasis will be placed on practical and computational aspects of Uncertainty Quantification and Propagation including the implementation of relevant algorithms on HPC architectures.
LernzielThe course will teach
- programming models and tools for multi and many-core architectures
- fundamental concepts of Uncertainty Quantification and Propagation (UQ+P) for computational models of systems in Engineering and Life Sciences
InhaltHigh Performance Computing:
- Advanced topics in shared-memory programming
- Advanced topics in MPI
- GPU architectures and CUDA programming

Uncertainty Quantification:
- Uncertainty quantification under parametric and non-parametric modeling uncertainty
- Bayesian inference with model class assessment
- Markov Chain Monte Carlo simulation
SkriptLink
Class notes, handouts
Literatur- Class notes
- Introduction to High Performance Computing for Scientists and Engineers, G. Hager and G. Wellein
- CUDA by example, J. Sanders and E. Kandrot
- Data Analysis: A Bayesian Tutorial, Devinderjit Sivia
151-0306-00LVisualization, Simulation and Interaction - Virtual Reality I Information W4 KP4GA. Kunz
KurzbeschreibungTechnologie der virtuellen Realität. Menschliche Faktoren, Erzeugung virtueller Welten, Beleuchtungsmodelle, Display- und Beschallungssysteme, Tracking, haptische/taktile Interaktion, Motion Platforms, virtuelle Prototypen, Datenaustausch, VR-Komplettsysteme, Augmented Reality; Kollaborationssysteme; VR und Design; Umsetzung der VR in der Industrie; Human COmputer Interfaces (HCI).
LernzielDie Studierenden erhalten einen Überblick über die virtuelle Realität, sowohl aus technischer als auch aus informationstechnologischer Sicht. Sie lernen unterschiedliche Software- und Hardwareelemente kennen sowie deren Einsatzmöglichkeiten im Geschäftsprozess. Die Studierenden entwickeln eine Kenntnis darüber, wo sich heute die virtuelle Realität nutzbringend einsetzen lässt und wo noch weiterer Forschungsbedarf besteht. Anhand konkreter Programme und Systeme erfahren die Teilnehmer den Umgang mit den erlernten neuen Technologien.
InhaltDiese Vorlesung gibt eine Einführung in die Technologie der virtuellen Realität als neues Tool zur Bewältigung komplexer Geschäftsprozesse. Es sind die folgenden Themen vorgesehen: Einführung und Geschichte der VR; Eingliederung der VR in die Produktentwicklung; Nutzen von VR für die Industrie; menschliche Faktoren als Grundlage der virtuellen Realität; Einführung in die Erzeugung (Modellierung) virtueller Welten; Beleuchtungsmodelle; Kollisionserkennung; Displaysysteme; Projektionssysteme; Beschallungssysteme; Trackingssysteme; Interaktionsgeräte für die virtuelle Umgebung; haptische und taktile Interaktion; Motion Platforms; Datenhandschuh; physikalisch basierte Simulation; virtuelle Prototypen; Datenaustausch und Datenkommunikation; VR-Komplettsysteme; Augmented Reality; Kollaborationssysteme; VR zur Unterstützung von Designaufgaben; Umsetzung der VR in der Industrie; Ausblick in die laufende Forschung im Bereich VR.

Lehrmodule:
- Geschichte der VR und Definition der wichtigsten Begriffe
- Einordnung der VR in Geschäftsprozesse
- Die Erzeugung virtueller Welten
- Geräte und Technologien für die immersive virtuelle Realität
- Anwendungen der VR in unterschiedlichsten Gebieten
SkriptDie Durchführung der Lehrveranstaltung erfolgt gemischt mit Vorlesungs- und Übungsanteilen.
Die Vorlesung kann auf Wunsch in Englisch erfolgen. Das Skript ist ebenfalls in Englisch verfügbar.
Skript, Handout; Kosten SFr.50.-
Voraussetzungen / BesonderesVoraussetzungen:
keine
Vorlesung geeignet für D-MAVT, D-ITET, D-MTEC und D-INF

Testat/ Kredit-Bedingungen/ Prüfung:
– Teilnahme an Vorlesung und Kolloquien
– Erfolgreiche Durchführung von Übungen in Teams
– Mündliche Einzelprüfung 30 Minuten
151-0534-00LAdvanced DynamicsW4 KP3V + 1UP. Tiso
KurzbeschreibungLagrangian dynamics - Principle of virtual work and virtual power - holonomic and non holonomic contraints - 3D rigid body dynamics - equilibrium - linearization - stability - vibrations - frequency response
LernzielThis course provides the students of mechanical engineering with fundamental analytical mechanics for the study of complex mechanical systems .We introduce the powerful techniques of principle of virtual work and virtual power to systematically write the equation of motion of arbitrary systems subjected to holonomic and non-holonomic constraints. The linearisation around equilibrium states is then presented, together with the concept of linearised stability. Linearized models allow the study of small amplitude vibrations for unforced and forced systems. For this, we introduce the concept of vibration modes and frequencies, modal superposition and modal truncation. The case of the vibration of light damped systems is discussed. The kinematics and dynamics of 3D rigid bodies is also extensively treated.
SkriptLecture notes are produced in class and are downloadable right after each lecture.
LiteraturThe students will prepare their own notes. A copy of the lecture notes will be available.
Voraussetzungen / BesonderesMechanics III or equivalent; Analysis I-II, or equivalent; Linear Algebra I-II, or equivalent.
151-0566-00LRecursive Estimation Information W4 KP2V + 1UR. D'Andrea
KurzbeschreibungEstimation of the state of a dynamic system based on a model and observations in a computationally efficient way.
LernzielLearn the basic recursive estimation methods and their underlying principles.
InhaltIntroduction to state estimation; probability review; Bayes' theorem; Bayesian tracking; extracting estimates from probability distributions; Kalman filter; extended Kalman filter; particle filter; observer-based control and the separation principle.
SkriptLecture notes available on course website: Link
Voraussetzungen / BesonderesRequirements: Introductory probability theory and matrix-vector algebra.
151-0623-00LETH Zurich Distinguished Seminar in Robotics, Systems and Controls Information
Students for other Master's programmes in Department Mechanical and Process Engineering cannot use the credit in the category Core Courses
W1 KP1SB. Nelson, M. Chli, R. Gassert, M. Hutter, W. Karlen, R. Riener, R. Siegwart
KurzbeschreibungThis course consists of a series of seven lectures given by researchers who have distinguished themselves in the area of Robotics, Systems, and Controls.
LernzielObtain an overview of various topics in Robotics, Systems, and Controls from leaders in the field. Please see Link for a list of upcoming lectures.
InhaltThis course consists of a series of seven lectures given by researchers who have distinguished themselves in the area of Robotics, Systems, and Controls. MSc students in Robotics, Systems, and Controls are required to attend every lecture. Attendance will be monitored. If for some reason a student cannot attend one of the lectures, the student must select another ETH or University of Zurich seminar related to the field and submit a one page description of the seminar topic. Please see Link for a suggestion of other lectures.
Voraussetzungen / BesonderesStudents are required to attend all seven lectures to obtain credit. If a student must miss a lecture then attendance at a related special lecture will be accepted that is reported in a one page summary of the attended lecture. No exceptions to this rule are allowed.
151-0630-00LNanorobotics Information W4 KP2V + 1US. Pané Vidal
KurzbeschreibungNanorobotics is an interdisciplinary field that includes topics from nanotechnology and robotics. The aim of this course is to expose students to the fundamental and essential aspects of this emerging field.
LernzielThe aim of this course is to expose students to the fundamental and essential aspects of this emerging field. These topics include basic principles of nanorobotics, building parts for nanorobotic systems, powering and locomotion of nanorobots, manipulation, assembly and sensing using nanorobots, molecular motors, and nanorobotics for nanomedicine.
151-0641-00LIntroduction to Robotics and Mechatronics Information Belegung eingeschränkt - Details anzeigen
Number of participants limited to 60.

Enrollment is only valid through registration on the MSRL Website (Link). Registration per e-mail is no longer accepted!
W4 KP2V + 2UB. Nelson, N. Shamsudhin
KurzbeschreibungThe aim of this lecture is to expose students to the fundamentals of mechatronic and robotic systems. Over the course of these lectures, topics will include how to interface a computer with the real world, different types of sensors and their use, different types of actuators and their use.
LernzielThe aim of this lecture is to expose students to the fundamentals of mechatronic and robotic systems. Over the course of these lectures, topics will include how to interface a computer with the real world, different types of sensors and their use, different types of actuators and their use, and forward and inverse kinematics. Throughout the course students will periodically attend laboratory sessions and implement lessons learned during lectures on real mechatronic systems.
InhaltAn ever increasing number of mechatronic systems are finding their way into our daily lives. Mechatronic systems synergistically combine computer science, electrical engineering, and mechanical engineering. Robotics systems can be viewed as a subset of mechatronics that focuses on sophisticated control of moving devices. The aim of this lecture is to expose students to the fundamentals of these systems. Over the course of these lectures, topics will include how to interface a computer with the real world, different types of sensors and their use, different types of actuators and their use, and forward and inverse kinematics. Throughout the course students will periodically attend laboratory sessions and implement lessons learned during lectures on real mechatronic systems.
Voraussetzungen / BesonderesThe registration is limited to 60 students.
There are 4 credit points for this lecture.
The lecture will be held in English.
The students are expected to be familiar with C programming.
151-0660-00LModel Predictive Control Information W4 KP2V + 1UM. Zeilinger
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).
151-0634-00LPerception and Learning for Robotics
Number of participants limited to: 30

To apply for the course please create a CV in pdf of max. 2 pages, including your machine learning and/or robotics experience. Please send the pdf to Link for approval.
W4 KP1AC. D. Cadena Lerma, I. Gilitschenski, R. Siegwart
KurzbeschreibungThis course covers tools from statistics and machine learning enabling the participants to deploy these algorithms as building blocks for perception pipelines on robotic tasks. All mathematical methods provided within the course will be discussed in context of and motivated by example applications mostly from robotics. The main focus of this course are student projects on robotics.
LernzielApplying Machine Learning methods for solving real-world robotics problems.
InhaltDeep Learning for Perception; (Deep) Reinforcement Learning; Graph-Based Simultaneous Localization and Mapping
SkriptSlides will be made available to the students.
LiteraturWill be announced in the first lecture.
Voraussetzungen / BesonderesThe students are expected to be familiar with material of the "Recursive Estimation" and the "Learning and Intelligent Systems" lectures. Particularly understanding of basic machine learning concepts, stochastic gradient descent for neural networks, reinforcement learning basics, and knowledge of Bayesian Filtering are required. Furtheremore, good knowledge of programming in C++ and Python is required.
151-0854-00LAutonomous Mobile Robots Information W5 KP4GR. Siegwart, M. Chli, J. Nieto
KurzbeschreibungThe objective of this course is to provide the basics required to develop autonomous mobile robots and systems. Main emphasis is put on mobile robot locomotion and kinematics, envionmen perception, and probabilistic environment modeling, localizatoin, mapping and navigation. Theory will be deepened by exercises with small mobile robots and discussed accross application examples.
LernzielThe objective of this course is to provide the basics required to develop autonomous mobile robots and systems. Main emphasis is put on mobile robot locomotion and kinematics, envionmen perception, and probabilistic environment modeling, localizatoin, mapping and navigation.
SkriptThis lecture is enhanced by around 30 small videos introducing the core topics, and multiple-choice questions for continuous self-evaluation. It is developed along the TORQUE (Tiny, Open-with-Restrictions courses focused on QUality and Effectiveness) concept, which is ETH's response to the popular MOOC (Massive Open Online Course) concept.
LiteraturThis lecture is based on the Textbook:
Introduction to Autonomous Mobile Robots
Roland Siegwart, Illah Nourbakhsh, Davide Scaramuzza, The MIT Press, Second Edition 2011, ISBN: 978-0262015356
151-1115-00LAusgewählte Kapitel der FlugtechnikW4 KP3GJ. Wildi
KurzbeschreibungBewegungsgleichungen. Flugleistungen und Flugbereiche. Statische Stabilität und Steuerbarkeit (Längs-, Lateral, Geschwindigkeits-, Windfahnenstabilität). Dynamische Längs- und Querstabilität.
Einführung in die Flug- und Windkanalmesstechnik.
Lernziel- Grundlagen vermitteln zur Lösung flugmechanischer Aufgabenstellungen
- Überblick geben über Methoden zur Behandlung von flugdynamischen Stabilitätsproblemen
- Durchführen von Flugleistungsberechnungen
- Einführen von Verfahren der Flugmesstechnik und Auswertung von Versuchen.
InhaltBewegungsgleichungen. Flugleistungen und Flugbereiche. Statische Stabilität und Steuerbarkeit (Längs-, Lateral, Geschwindigkeits-, Windfahnenstabilität). Dynamische Längs- und Querstabilität.
Einführung in die Flug- und Windkanalmesstechnik.
SkriptAusgewählte Kapitel der Flugtechnik (J. Wildi)
Voraussetzungen / BesonderesEmpfohlen: Vorlesung 'Grundlagen der Flugzeug- und Fahrzeugaerodynamik' (FS)
227-0124-00LEmbedded Systems Information W6 KP4GL. Thiele
KurzbeschreibungAn embedded system is some combination of computer hardware and software, either fixed in capability or programmable, that is designed for a specific function or for specific functions within a larger system. The course covers theoretical and practical aspects of embedded system design and includes a series of lab sessions.
LernzielUnderstanding specific requirements and problems arising in embedded system applications.

Understanding architectures and components, their hardware-software interfaces, the memory architecture, communication between components, embedded operating systems, real-time scheduling theory, shared resources, low-power and low-energy design as well as hardware architecture synthesis.

Using the formal models and methods in embedded system design in practical applications using the programming language C, the operating system FreeRTOS, a commercial embedded system platform and the associated design environment.
InhaltAn embedded system is some combination of computer hardware and software, either fixed in capability or programmable, that is designed for a specific function or for specific functions within a larger system. For example, they are part of industrial machines, agricultural and process industry devices, automobiles, medical equipment, cameras, household appliances, airplanes, sensor networks, internet-of-things, as well as mobile devices.

The focus of this lecture is on the design of embedded systems using formal models and methods as well as computer-based synthesis methods. Besides, the lecture is complemented by laboratory sessions where students learn to program in C, to base their design on the embedded operating systems FreeRTOS, to use a commercial embedded system platform including sensors, and to edit/debug via an integrated development environment.

Specifically the following topics will be covered in the course: Embedded system architectures and components, hardware-software interfaces and memory architecture, software design methodology, communication, embedded operating systems, real-time scheduling, shared resources, low-power and low-energy design, hardware architecture synthesis.

More information is available at Link .
SkriptThe following information will be available: Lecture material, publications, exercise sheets and laboratory documentation at Link .
LiteraturP. Marwedel: Embedded System Design, Springer, ISBN 978-3-319-56045-8, 2018.

G.C. Buttazzo: Hard Real-Time Computing Systems. Springer Verlag, ISBN 978-1-4614-0676-1, 2011.

Edward A. Lee and Sanjit A. Seshia: Introduction to Embedded Systems, A Cyber-Physical Systems Approach, Second Edition, MIT Press, ISBN 978-0-262-53381-2, 2017.

M. Wolf: Computers as Components – Principles of Embedded System Design. Morgan Kaufman Publishers, ISBN 978-0-128-05387-4, 2016.
Voraussetzungen / BesonderesPrerequisites: Basic knowledge in computer architectures and programming.
227-0207-00LNonlinear Systems and Control Information
Voraussetzung: Control Systems (227-0103-00L)
W6 KP4GE. Gallestey Alvarez, P. F. Al Hokayem
KurzbeschreibungIntroduce students to the area of nonlinear systems and their control. Familiarize them with tools for modelling and analysis of nonlinear systems. Provide an overview of the various nonlinear controller design methods.
LernzielOn completion of the course, students understand the difference between linear and nonlinear systems, know the the mathematical techniques for modeling and analysing these systems, and have learnt various methods for designing controllers for these systems.
Course puts the student in the position to deploy nonlinear control techniques in real applications. Theory and exercises are combined for better understanding of virtues and drawbacks in the different methods.
InhaltVirtually all practical control problems are of nonlinear nature. In some cases the application of linear control methods will lead to satisfying controller performance. In many other cases however, only application of nonlinear analysis and synthesis methods will guarantee achievement of the desired objectives. During the past decades a number of mature nonlinear controller design methods have been developed and have proven themselves in applications. After an introduction of the basic methods for modelling and analysing nonlinear systems, these methods will be introduced together with a critical discussion of their pros and cons, and the students will be familiarized with the basic concepts of nonlinear control theory.

This course is designed as an introduction to the nonlinear control field and thus no prior knowledge of this area is required. The course builds, however, on a good knowledge of the basic concepts of linear control.
SkriptAn english manuscript will be made available on the course homepage during the course.
LiteraturH.K. Khalil: Nonlinear Systems, Prentice Hall, 2001.
Voraussetzungen / BesonderesPrerequisites: Linear Control Systems, or equivalent.
227-0216-00LControl Systems II Information W6 KP4GR. Smith
KurzbeschreibungIntroduction to basic and advanced concepts of modern feedback control.
LernzielIntroduction to basic and advanced concepts of modern feedback control.
InhaltThis course is designed as a direct continuation of the course "Regelsysteme" (Control Systems). The primary goal is to further familiarize students with various dynamic phenomena and their implications for the analysis and design of feedback controllers. Simplifying assumptions on the underlying plant that were made in the course "Regelsysteme" are relaxed, and advanced concepts and techniques that allow the treatment of typical industrial control problems are presented. Topics include control of systems with multiple inputs and outputs, control of uncertain systems (robustness issues), limits of achievable performance, and controller implementation issues.
SkriptThe slides of the lecture are available to download.
LiteraturSkogestad, Postlethwaite: Multivariable Feedback Control - Analysis and Design. Second Edition. John Wiley, 2005.
Voraussetzungen / BesonderesPrerequisites:
Control Systems or equivalent
227-0224-00LStochastic Systems Information W4 KP2V + 1UF. Herzog
KurzbeschreibungProbability. Stochastic processes. Stochastic differential equations. Ito. Kalman filters. St Stochastic optimal control. Applications in financial engineering.
LernzielStochastic dynamic systems. Optimal control and filtering of stochastic systems. Examples in technology and finance.
Inhalt- Stochastic processes
- Stochastic calculus (Ito)
- Stochastic differential equations
- Discrete time stochastic difference equations
- Stochastic processes AR, MA, ARMA, ARMAX, GARCH
- Kalman filter
- Stochastic optimal control
- Applications in finance and engineering
SkriptH. P. Geering et al., Stochastic Systems, Measurement and Control Laboratory, 2007 and handouts
227-0248-00LPower Electronic Systems II Information W6 KP4GJ. W. Kolar
KurzbeschreibungThis course details structures, operating ranges, and control concepts of modern power electronic systems to provide a deeper understanding of power electronic circuits and power components. Most recent concepts of high switching frequency AC/DC converters and AC/AC matrix inverters are presented. Simulation exercises, implemented in GeckoCIRCUITS, are used to consolidate the concepts discussed.
LernzielThe objective of this course is to convey knowledge of structures, operating ranges, and control concepts of modern power electronic systems. Further objectives are: to know most recent concepts and operation modes of high switching frequency AC/DC converters and AC/AC matrix inverters; to develop a deeper understanding of multi-pulse power converter circuits, transformers, and electromechanical energy converters; and to understand in-depth details of power electronic systems. Simulation exercises, implemented in the electric circuit simulator GeckoCIRCUITS, are used to consolidate the presented theoretical concepts.
InhaltConverter dynamics and control: State Space Averaging, transfer functions, controller design, impact of the input filter on the converter transfer functions.
Performance data of single-phase and three-phase systems: effect of different loss components on the efficiency characteristics, linear and non-linear single phase loads, power flow of general three-phase systems, space vector calculus.
Modeling and control of three-phase PWM rectifiers: system characterization using rotating coordinates, control structure, transfer functions, operation with symmetrical and unsymmetrical mains voltages.
Scaling laws of transformers and electromechanical actuators.
Drives with permanent magnet synchronous machines: basic function, modeling, field-oriented control.
Unidirectional AC/DC converters and AC/AC converters: voltage and current DC link converters, indirect and direct matrix converters.
SkriptLecture notes and associated exercises including correct answers, simulation program for interactive self-learning including visualization/animation features.
Voraussetzungen / BesonderesPrerequisites: Introductory course on power electronics.
227-0528-00LPower System Dynamics, Control and Operation Information W6 KP4GG. Hug, A. Ulbig
KurzbeschreibungThe electric power system is a system that is never in steady state due to constant changes in load and generation inputs. This course is dedicated to the dynamical properties of the electric power grid including how the system state is estimated, generation/load balance is ensured by frequency control and how the system reacts in case of faults in the system. The course includes two excursions.
LernzielThe learning objectives of the course are to understand and be able to apply the dynamic modeling of power systems, to compute and discuss the actions of generators based on frequency control, to describe the workings of a synchronous machine and the implications on the grid, to describe and apply state estimation procedures, to discuss the IT infrastructure and protection algorithms in power systems.
InhaltThe electric power system is a system that is never in steady state due to constant changes in load and generation inputs. Consequently, the monitoring and operation of the electric power grid is a challenging task. The course starts with the introduction of general operational procedures and the discussion of state estimation which is an important tool to observe the state of the grid. The course is then dedicated to the modeling and studying of the dynamical properties of the electric power grid. Frequency control which ensures the generation/load balance in real time is the basis for real-time control and is presented in depth. For the analysis of how the system detects and reacts dynamically in fault situations, protection and dynamic models for synchronous machines are introduced.
SkriptLecture notes. WWW pages.
227-0529-00LLiberalized Electric Power Systems and Smart Grids Information W6 KP4GR. Bacher
KurzbeschreibungThis class begins by discussing the paths from monopolies towards liberalized electric power markets with the grid as natural monopoly. After going through detailed mainly transmission grid constrained market models, SmartGrids models and approaches are introduced for the future distribution grid.
Lernziel- Understanding the legal, physical and market based framework for transmission based electric power systems.
- Understanding the market models for a secure and market based day-ahead operation of Smart Power Systems.
- Understanding Smart Grids and their market-compatible models
- Gaining experience with the formulation, implementation and computation of constrained electricity markets for transmission and Smart distribution systems.
Inhalt- Legal conditions for the regulation and operation of electric power systems (CH, EU).
- Modelling physical laws, objectives and constraints of electric power systems at transmission and smart distribution level.
- Optimization as mathematical tool to achieve maximum society profits and considering at the same time grid based constraints and incentives towards distributed / renewable energy ressources.
- Various electricity market models, their advantages and disadvantages.
- SmartGrids: The new energy system and compatibility issues with traditional market models and regulation.
SkriptClass material is continuously updated and distributed to students.
Voraussetzungen / BesonderesRequirements: Programming in any language, Numerical analysis, basics for power system models, optimization and economics, active participation (discussions)

Mode of exam: examination may be computer-based
227-0690-09LAdvanced Topics in Control (Spring 2018) Information
New topics are introduced every year.
W4 KP2V + 2UF. Dörfler
KurzbeschreibungThis class will introduce students to advanced, research level topics in the area of automatic control. Coverage varies from semester to semester, repetition for credit is possible, upon consent of the instructor. During the Spring Semester 2018 the class will concentrate on distributed systems and control.
LernzielThe intent is to introduce students to advanced research level topics in the area of automatic control. The course is jointly organized by Prof. R. D'Andrea, L. Guzzella, J. Lygeros, M. Morari, R. Smith, and F. Dörfler. Coverage and instructor varies from semester to semester. Repetition for credit is possible, upon consent of the instructor. During the Spring Semester 2018 the class will be taught by F. Dörfler and will focus on distributed systems and control.
InhaltDistributed control systems include large-scale physical systems, engineered multi-agent systems, as well as their interconnection in cyber-physical systems. Representative examples are the electric power grid, camera networks, and robotic sensor networks. The challenges associated with these systems arise due to their coupled, distributed, and large-scale nature, and due to limited sensing, communication, and control capabilities. This course covers modeling, analysis, and design of distributed control systems.

Topics covered in the course include:
- the theory of graphs (with an emphasis on algebraic and spectral graph theory);
- basic models of multi-agent and interconnected dynamical systems;
- continuous-time and discrete-time distributed averaging algorithms (consensus);
- coordination algorithms for rendezvous, formation, flocking, and deployment;
- applications in robotic coordination, coupled oscillators, social networks, sensor networks, electric power grids, epidemics, and positive systems.
SkriptA set of self-contained set of lecture notes will be made available.
LiteraturRelevant papers and books will be made available through the course website.
Voraussetzungen / BesonderesControl systems (227-0216-00L), Linear system theory (227-0225-00L), or equivalents, as well as sufficient mathematical maturity.
227-0694-00LGame Theory and Control Information W4 KP2V + 2US. Bolognani, A. R. Hota, M. Kamgarpour
KurzbeschreibungGame Theory is the study of strategic decision making, and was used to solve problems in economics by John Nash (A Beautiful Mind) and others. We study concepts and methods in Game Theory, and show how these can be used to solve control design problems. The course covers non-cooperative dynamic games and Nash equilibria, and emphasizes their use in control applications.
LernzielFormulate an optimal control problem as a noncooperative dynamic game, compute mixed and behavioural strategies for different equilibria.
InhaltIntroduction to game theory, mathematical tools including convex optimisation and dynamic programming, zero sum games in matrix and extensive form, pure and mixed strategies, minimax theorem, nonzero sum games in normal and extensive form, numerical computation of mixed equilibrium strategies, Nash and Stackelberg equilibria, potential games, infinite dynamic games, differential games, behavioral strategies and informational properties for dynamic games, aggregative games, VCG mechanism.
SkriptWill be made available from SPOD or course webpage.
LiteraturBasar, T. and Olsder, G. Dynamic Noncooperative Game Theory, 2nd
Edition, Society for Industrial and Applied Mathematics, 1998. Available through ETH Bibliothek directly at Link.
Voraussetzungen / BesonderesControl Systems I (or equivalent). Necessary methods and concepts from optimization will be covered in the course.
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