Suchergebnis: Katalogdaten im Herbstsemester 2020

Maschineningenieurwissenschaften Master Information
Kernfächer
Robotics, Systems and Control
Die unter der Kategorie “Kernfächer” gelisteten Fächer sind empfohlen. Andere Kurse sind nicht ausgeschlossen, benötigen jedoch die Zustimmung des Tutors/der Tutorin.
NummerTitelTypECTSUmfangDozierende
151-0107-20LHigh Performance Computing for Science and Engineering (HPCSE) I Information W4 KP4GP. Koumoutsakos, S. M. Martin
KurzbeschreibungThis course gives an introduction into algorithms and numerical methods for parallel computing on shared and distributed memory architectures. The algorithms and methods are supported with problems that appear frequently in science and engineering.
LernzielWith manufacturing processes reaching its limits in terms of transistor density on today’s computing architectures, efficient utilization of computing resources must include parallel execution to maintain scaling. The use of computers in academia, industry and society is a fundamental tool for problem solving today while the “think parallel” mind-set of developers is still lagging behind.

The aim of the course is to introduce the student to the fundamentals of parallel programming using shared and distributed memory programming models. The goal is on learning to apply these techniques with the help of examples frequently found in science and engineering and to deploy them on large scale high performance computing (HPC) architectures.
Inhalt1. Hardware and Architecture: Moore’s Law, Instruction set architectures (MIPS, RISC, CISC), Instruction pipelines, Caches, Flynn’s taxonomy, Vector instructions (for Intel x86)

2. Shared memory parallelism: Threads, Memory models, Cache coherency, Mutual exclusion, Uniform and Non-Uniform memory access, Open Multi-Processing (OpenMP)

3. Distributed memory parallelism: Message Passing Interface (MPI), Point-to-Point and collective communication, Blocking and non-blocking methods, Parallel file I/O, Hybrid programming models

4. Performance and parallel efficiency analysis: Performance analysis of algorithms, Roofline model, Amdahl’s Law, Strong and weak scaling analysis

5. Applications: HPC Math libraries, Linear Algebra and matrix/vector operations, Singular value decomposition, Neural Networks and linear autoencoders, Solving partial differential equations (PDEs) using grid-based and particle methods
SkriptLink
Class notes, handouts
Literatur• An Introduction to Parallel Programming, P. Pacheco, Morgan Kaufmann
• Introduction to High Performance Computing for Scientists and Engineers, G. Hager and G. Wellein, CRC Press
• Computer Organization and Design, D.H. Patterson and J.L. Hennessy, Morgan Kaufmann
• Vortex Methods, G.H. Cottet and P. Koumoutsakos, Cambridge University Press
• Lecture notes
Voraussetzungen / BesonderesStudents should be familiar with a compiled programming language (C, C++ or Fortran). Exercises and exams will be designed using C++. The course will not teach basics of programming. Some familiarity using the command line is assumed. Students should also have a basic understanding of diffusion and advection processes, as well as their underlying partial differential equations.
151-0323-00LAutonomous Mobility on Demand: From Car to Fleet Information Belegung eingeschränkt - Details anzeigen
Number of participants limited to 30.
W4 KP4GJ. Tani, A. Censi
KurzbeschreibungAutonomous Mobility on Demand systems based on self-driving cars will make a huge impact in the world. This class describes the basics of modeling, perception, planning, control and learning for self-driving cars. The focus is on integration and co-design of components and behaviors. The course has a heavy experimental component based on the Duckietown platform.
LernzielThe students will learn how to design, implement and operate all parts of an architecture for a complex multi-robot system performing non trivial tasks.
InhaltDevelopment tools and best practices for software development of open source projects; single autonomous car functionalities (perception, planning, modeling and control, based primarily on vision data, complemented by learning based approaches).
SkriptCourse notes will be provided for free in an electronic form. Each student will receive a Duckiebot and a small city loop.
LiteraturCourse notes will be provided for free in an electronic form. These are some books that can be used to provide background information or consulted as references: (1) Siegwart, Nourbakhsh, Scaramuzza - Introduction to autonomous mobile robots; (2) Norvig, Russell - Artificial Intelligent, a modern approach. (3) Peter Corke - Robotics Vision and Control (4) Oussama Khatib, Bruno Siciliano - Handbook of Robotics
Voraussetzungen / BesonderesThis course is also known as "Duckietown". Students should have taken a basic course in probability theory, computer vision, control systems, and should be familiar with basic programming (Python) and Linux use.

The course will be fully remote. Students will need ~5 square meters of free space at their place of work to set up the Duckietown platform, necessary to perform the learning activities and exercises.
151-0371-00LAdvanced Model Predictive Control Belegung eingeschränkt - Details anzeigen W4 KP2V + 1UM. Zeilinger, A. Carron, L. Hewing
KurzbeschreibungModel 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.
LernzielDesign, implement and analyze advanced MPC formulations for robust and stochastic uncertainty descriptions, in particular with data-driven formulations.
InhaltTopics 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
SkriptLecture notes will be provided.
Voraussetzungen / BesonderesBasic 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.
151-0532-00LNonlinear Dynamics and Chaos I Information W4 KP2V + 2UG. Haller
KurzbeschreibungBasic facts about nonlinear systems; stability and near-equilibrium dynamics; bifurcations; dynamical systems on the plane; non-autonomous dynamical systems; chaotic dynamics.
LernzielThis course is intended for Masters and Ph.D. students in engineering sciences, physics and applied mathematics who are interested in the behavior of nonlinear dynamical systems. It offers an introduction to the qualitative study of nonlinear physical phenomena modeled by differential equations or discrete maps. We discuss applications in classical mechanics, electrical engineering, fluid mechanics, and biology. A more advanced Part II of this class is offered every other year.
Inhalt(1) Basic facts about nonlinear systems: Existence, uniqueness, and dependence on initial data.

(2) Near equilibrium dynamics: Linear and Lyapunov stability

(3) Bifurcations of equilibria: Center manifolds, normal forms, and elementary bifurcations

(4) Nonlinear dynamical systems on the plane: Phase plane techniques, limit sets, and limit cycles.

(5) Time-dependent dynamical systems: Floquet theory, Poincare maps, averaging methods, resonance
SkriptThe class lecture notes will be posted electronically after each lecture. Students should not rely on these but prepare their own notes during the lecture.
Voraussetzungen / Besonderes- Prerequisites: Analysis, linear algebra and a basic course in differential equations.

- Exam: two-hour written exam in English.

- Homework: A homework assignment will be due roughly every other week. Hints to solutions will be posted after the homework due dates.
151-0563-01LDynamic Programming and Optimal Control Information W4 KP2V + 1UR. D'Andrea
KurzbeschreibungIntroduction to Dynamic Programming and Optimal Control.
LernzielCovers the fundamental concepts of Dynamic Programming & Optimal Control.
InhaltDynamic Programming Algorithm; Deterministic Systems and Shortest Path Problems; Infinite Horizon Problems, Bellman Equation; Deterministic Continuous-Time Optimal Control.
LiteraturDynamic Programming and Optimal Control by Dimitri P. Bertsekas, Vol. I, 3rd edition, 2005, 558 pages, hardcover.
Voraussetzungen / BesonderesRequirements: Knowledge of advanced calculus, introductory probability theory, and matrix-vector algebra.
151-0567-00LEngine Systems Information W4 KP3GC. Onder
KurzbeschreibungEinführung in heutige und zukünftige Verbrennungsmotorsysteme, insbesondere deren elektronische Steuerungen und Regelungen
LernzielModerne Methoden der Systemoptimierung und Regelung am Beispiel "Verbrennungsmotor" kennenlernen und an realen Motoren einüben. Aufbau und Funktionsweise von Antriebssystemen verstehen und quantitativ beschreiben können.
InhaltPhysikalische Phänomene und mathematische Modelle von Komponenten und Systemen (Gemischbildung, Laststeuerung, Aufladung, Emissionen, Antriebsstrangkomponenten, etc.). Fallstudien zum Thema modellbasierte optimale Auslegung und Steuerung / Regelung von Motorsystemen mit dem Ziel, Verbrauch und Schadstoffemissionen zu minimieren.
SkriptIntroduction to Modeling and Control of Internal Combustion Engine Systems
Guzzella Lino, Onder Christopher H.
2010, Second Edition, 354 p., hardbound
ISBN: 978-3-642-10774-0
Voraussetzungen / BesonderesKombinierte Haus- und Laborübung Motoren (Lambda- oder Leerlaufdrehzahlregelung), in Gruppen
151-0569-00LVehicle Propulsion Systems Information W4 KP3GC. Onder, P. Elbert
KurzbeschreibungEinführung in heutige und zukünftige Fahrzeugantriebssysteme, insbesondere in elektronische Steuerungen und Regelungen der Längsdynamik
LernzielModerne Methoden der Systemoptimierung und Regelung am Beispiel "Fahrzeug" kennenlernen. Aufbau und Funktionsweise von konventionellen und neuen Antriebssystemen verstehen und quantitativ beschreiben können
InhaltPhysikalische Phänomene und mathematische Modelle von Komponenten und Systemen (Schalt-, Automaten- und kontinuierliche Getriebe, unkonventionelle Energiespeicher, Elektroantriebe, Batterien, Hybridantriebe, Brennstoffzellensysteme, Rad/Strasse-Schnittstellen, automatische Bremssysteme (ABS), etc.).

Mathematische Methoden, CAE-Tools und Fallstudien zum Thema modellbasierte Auslegung und Steuerung / Regelung von Fahrzeugsystemen mit dem Ziel, Verbrauch und Schadstoffemissionen zu minimieren.
SkriptVehicle Propulsion Systems --
Introduction to Modeling and Optimization
Guzzella Lino, Sciarretta Antonio
2013, X, 409 p. 202 illus., Geb.
ISBN: 978-3-642-35912-5
Voraussetzungen / BesonderesVorlesungen von Prof. Dr. Ch. Onder und Dr. Ph. Elbert auch in Deutsch möglich.
151-0573-00LSystem Modeling Information W4 KP2V + 1UL. Guzzella
KurzbeschreibungEinführung in die Systemmodellierung für die Steuerung. Generische Modellierungsansätze auf der Grundlage erster Prinzipien, Lagrangealer Formalismus, Energieansätze und experimentelle Daten. Modellparametrierung und Parametrierung. Grundlegende Analyse von linearen und nichtlinearen Systemen.
LernzielErfahren Sie, wie man mathematisch ein physisches System oder einen Prozess in Form eines Modells beschreibt, das für Analyse- und Kontrollzwecke verwendbar ist.
InhaltDiese Klasse führt generische Systemmodellierungsansätze für steuerungsorientierte Modelle ein, die auf ersten Prinzipien und experimentellen Daten basieren. Die Klasse umfasst zahlreiche Beispiele für mechatronische, thermodynamische, chemische, flüssigkeitsdynamische, energie- und verfahrenstechnische Systeme. Modellskalierung, Linearisierung, Auftragsreduktion und Ausgleich. Parameterschätzung mit Methoden der kleinsten Quadrate. Verschiedene Fallstudien: Lautsprecher, Turbinen, Wasser angetriebene Rakete, geostationäre Satelliten usw. Die Übungen behandeln praktische Beispiele.
SkriptDas Skript in englischer Sprache wird in der ersten Lektion verkauft.
LiteraturEine Literaturliste ist im Skript enthalten.
151-0593-00LEmbedded Control Systems
Findet dieses Semester nicht statt.
W4 KP6G
KurzbeschreibungThis course provides a comprehensive overview of embedded control systems. The concepts introduced are implemented and verified on a microprocessor-controlled haptic device.
LernzielFamiliarize students with main architectural principles and concepts of embedded control systems.
InhaltAn embedded system is a microprocessor used as a component in another piece of technology, such as cell phones or automobiles. In this intensive two-week block course the students are presented the principles of embedded digital control systems using a haptic device as an example for a mechatronic system. A haptic interface allows for a human to interact with a computer through the sense of touch.

Subjects covered in lectures and practical lab exercises include:
- The application of C-programming on a microprocessor
- Digital I/O and serial communication
- Quadrature decoding for wheel position sensing
- Queued analog-to-digital conversion to interface with the analog world
- Pulse width modulation
- Timer interrupts to create sampling time intervals
- System dynamics and virtual worlds with haptic feedback
- Introduction to rapid prototyping
SkriptLecture notes, lab instructions, supplemental material
Voraussetzungen / BesonderesPrerequisite courses are Control Systems I and Informatics I.

This course is restricted to 33 students due to limited lab infrastructure. Interested students please contact Marianne Schmid (E-Mail: Link)
After your reservation has been confirmed please register online at Link.

Detailed information can be found on the course website
Link
151-0601-00LTheory of Robotics and Mechatronics Information W4 KP3GP. Korba, S. Stoeter
KurzbeschreibungThis course provides an introduction and covers the fundamentals of the field, including rigid motions, homogeneous transformations, forward and inverse kinematics of multiple degree of freedom manipulators, velocity kinematics, motion planning, trajectory generation, sensing, vision, and control.
LernzielRobotics is often viewed from three perspectives: perception (sensing), manipulation (affecting changes in the world), and cognition (intelligence). Robotic systems integrate aspects of all three of these areas. This course provides an introduction to the theory of robotics, and covers the fundamentals of the field, including rigid motions, homogeneous transformations, forward and inverse kinematics of multiple degree of freedom manipulators, velocity kinematics, motion planning, trajectory generation, sensing, vision, and control.
InhaltAn introduction to the theory of robotics, and covers the fundamentals of the field, including rigid motions, homogeneous transformations, forward and inverse kinematics of multiple degree of freedom manipulators, velocity kinematics, motion planning, trajectory generation, sensing, vision, and control.
Skriptavailable.
151-0604-00LMicrorobotics Information W4 KP3GB. Nelson, N. Shamsudhin
KurzbeschreibungMicrorobotics is an interdisciplinary field that combines aspects of robotics, micro and nanotechnology, biomedical engineering, and materials science. The aim of this course is to expose students to the fundamentals of this emerging field. Throughout the course, the students apply these concepts in assignments. The course concludes with an end-of-semester examination.
LernzielThe objective of this course is to expose students to the fundamental aspects of the emerging field of microrobotics. This includes a focus on physical laws that predominate at the microscale, technologies for fabricating small devices, bio-inspired design, and applications of the field.
InhaltMain topics of the course include:
- Scaling laws at micro/nano scales
- Electrostatics
- Electromagnetism
- Low Reynolds number flows
- Observation tools
- Materials and fabrication methods
- Applications of biomedical microrobots
SkriptThe powerpoint slides presented in the lectures will be made available as pdf files. Several readings will also be made available electronically.
Voraussetzungen / BesonderesThe lecture will be taught in English.
151-0632-00LVision Algorithms for Mobile Robotics Information Belegung eingeschränkt - Details anzeigen
Number of participants limited to 55
Registration is on a first come, first served basis and SPACE IS LIMITED!
W4 KP2V + 2UD. Scaramuzza
KurzbeschreibungFor a robot to be autonomous, it has to perceive and understand the world around it. This course introduces you to the key computer vision algorithms used in mobile robotics, such as feature extraction, structure from motion, dense reconstruction, tracking, image retrieval, event-based vision, and visual-inertial odometry (the algorithms behind Hololens, Oculus Quest, and the NASA Mars rovers).
LernzielLearn the fundamental computer vision algorithms used in mobile robotics, in particular: filtering, feature extraction, structure from motion, multiple view geometry, dense reconstruction, tracking, image retrieval, event-based vision, and visual-inertial odometry and Simultaneous Localization And Mapping (SLAM) (the algorithms behind Hololens, Facebook-Oculus Quest, and the NASA Mars rovers).
InhaltEach lecture will be followed by a lab session where you will learn to implement a building block of a visual odometry algorithm in Matlab. By the end of the course, you will integrate all these building blocks into a working visual odometry algorithm.
SkriptLecture slides will be made available on the course official website: Link
Literatur[1] Computer Vision: Algorithms and Applications, by Richard Szeliski, Springer, 2010.
[2] Robotics Vision and Control: Fundamental Algorithms, by Peter Corke 2011.
[3] An Invitation to 3D Vision, by Y. Ma, S. Soatto, J. Kosecka, S.S. Sastry.
[4] Multiple view Geometry, by R. Hartley and A. Zisserman.
[5] Introduction to autonomous mobile robots 2nd Edition, by R. Siegwart, I.R. Nourbakhsh, and D. Scaramuzza, February, 2011
Voraussetzungen / BesonderesFundamentals of algebra, geomertry, matrix calculus, and Matlab programming.
151-0655-00LSkills for Creativity and Innovation Belegung eingeschränkt - Details anzeigen W4 KP3GI. Goller, C. Kobe
KurzbeschreibungThis lecture aims to enhance the knowledge and competency of students regarding their innovation capability. An overview on prerequisites of and different skills for creativity and innovation in individual & team settings is given. The focus of this lecture is clearly on building competencies - not just acquiring knowledge.
Lernziel- Basic knowledge about creativity and skills
- Knowledge about individual prerequisites for creativity
- Development of individual skills for creativity
- Knowledge about teams
- Development of team-oriented skills for creativity
- Knowledge and know-how about transfer to idea generation teams
InhaltBasic knowledge about creativity and skills:
- Introduction into creativity & innovation: definitions and models

Knowledge about individual prerequisites for creativity:
- Personality, motivation, intelligence

Development of individual skills for creativity:
- Focus on creativity as problem analysis & solving
- Individual skills in theoretical models
- Individual competencies: exercises and reflection

Knowledge about teams:
- Definitions and models
- Roles in innovation processes

Development of team-oriented skills for creativity:
- Idea generation and development in teams
- Cooperation & communication in innovation teams

Knowledge and know-how about transfer to idea generation teams:
- Self-reflection & development planning
- Methods of knowledge transfer
SkriptSlides, script and other documents will be distributed via moodle.ethz.ch
(access only for students registered to this course)
LiteraturGoller, I. & Bessant, J. (2017). Creativity for Innovation Management. Routledge. (ISBN-13: 978-1138641327)
As well as material handed out in the lecture
151-0727-00LFertigungstechnisches KolloquiumW4 KP3SK. Wegener, A. Kunz
KurzbeschreibungWeiterbildungsveranstaltung zu ausgewählten aktuellen Themen der Fertigungstechnik. Pro Nachmittag wird ein ausgewähltes Thema in mehreren Vorträgen, mehrheitlich durch Referenten aus der Industrie, vorgestellt und diskutiert.
Die Studierenden erstellen eine Zusammenfassung der Vorträge und bereiten sich auf die Prüfung mit Hilfe dieser Aufzeichnungen und eigenen Recherchen vor.
LernzielStändige Weiterbildung zu aktuellen Themen der Fertigungstechnik. Wissens- und Erfahrungsaustausch mit der Industrie und anderen Hochschulen.
InhaltAusgewählte aktuelle Themen der Fertigungstechnik, d.h. ständig wechselnder Inhalt.
Skriptkein Skript
Voraussetzungen / Besonderes- Studierende müssen die Kurse Fertigungstechnik I, Produktionsmaschinen I und Umformtechnik III - Umformtechnische Verfahren besucht und abgeschlossen haben.

- Weiterbildungsveranstaltung mit Fachvorträgen und grosser Beteiligung aus der Industrie.
151-0851-00LRobot Dynamics Information Belegung eingeschränkt - Details anzeigen W4 KP2V + 2UM. Hutter, R. Siegwart
KurzbeschreibungWe will provide an overview on how to kinematically and dynamically model typical robotic systems such as robot arms, legged robots, rotary wing systems, or fixed wing.
LernzielThe primary objective of this course is that the student deepens an applied understanding of how to model the most common robotic systems. The student receives a solid background in kinematics, dynamics, and rotations of multi-body systems. On the basis of state of the art applications, he/she will learn all necessary tools to work in the field of design or control of robotic systems.
InhaltThe course consists of three parts: First, we will refresh and deepen the student's knowledge in kinematics, dynamics, and rotations of multi-body systems. In this context, the learning material will build upon the courses for mechanics and dynamics available at ETH, with the particular focus on their application to robotic systems. The goal is to foster the conceptual understanding of similarities and differences among the various types of robots. In the second part, we will apply the learned material to classical robotic arms as well as legged systems and discuss kinematic constraints and interaction forces. In the third part, focus is put on modeling fixed wing aircraft, along with related design and control concepts. In this context, we also touch aerodynamics and flight mechanics to an extent typically required in robotics. The last part finally covers different helicopter types, with a focus on quadrotors and the coaxial configuration which we see today in many UAV applications. Case studies on all main topics provide the link to real applications and to the state of the art in robotics.
Voraussetzungen / BesonderesThe contents of the following ETH Bachelor lectures or equivalent are assumed to be known: Mechanics and Dynamics, Control, Basics in Fluid Dynamics.
151-0917-00LMass TransferW4 KP2V + 2US. E. Pratsinis, A. Güntner, V. Mavrantzas
KurzbeschreibungThis course presents the fundamentals of transport phenomena with emphasis on mass transfer. The physical significance of basic principles is elucidated and quantitatively described. Furthermore the application of these principles to important engineering problems is demonstrated.
LernzielThis course presents the fundamentals of transport phenomena with emphasis on mass transfer. The physical significance of basic principles is elucidated and quantitatively described. Furthermore the application of these principles to important engineering problems is demonstrated.
InhaltFick's laws; application and significance of mass transfer; comparison of Fick's laws with Newton's and Fourier's laws; derivation of Fick's 2nd law; diffusion in dilute and concentrated solutions; rotating disk; dispersion; diffusion coefficients, viscosity and heat conduction (Pr and Sc numbers); Brownian motion; Stokes-Einstein equation; mass transfer coefficients (Nu and Sh numbers); mass transfer across interfaces; Analogies for mass-, heat-, and momentum transfer in turbulent flows; film-, penetration-, and surface renewal theories; simultaneous mass, heat and momentum transfer (boundary layers); homogeneous and heterogeneous reversible and irreversible reactions; diffusion-controlled reactions; mass transfer and first order heterogeneous reaction. Applications.
LiteraturCussler, E.L.: "Diffusion", 3nd edition, Cambridge University Press, 2009.
Voraussetzungen / BesonderesStudents attending this highly-demanding course are expected to allocate sufficient time within their weekly schedule to successfully conduct the exercises.
151-1116-00LEinführung in Flug- und FahrzeugaerodynamikW4 KP3GJ. Wildi
KurzbeschreibungFlugzeugaerodynamik: Atmosphäre; Aerodynamische Kräfte (Auftrieb: Profile, Flügel. Widerstand: Restwiderstand, induzierter Widerstand);Schub.
Fahrzeugaerodynamik: Grundlagen: Luft- und Massenkräfte, Widerstand , Auftrieb. Aerodynamik und Fahrleistungen. Personenwagen; Nutzfahrzeuge; Rennfahrzeuge.
LernzielEinführung in die Grundlagen und Zusammenhänge der Flugzeug- und Fahrzeugaerodynamik vermitteln.
Grundlegende Zusammenhänge der Entstehung aerodynamischer Kräfte (insbesondere Auftrieb, Widerstand) verstehen und diese für einfache Konfigurationen von Flugzeugen und Fahrzeugen berechnen können. Den Einfluss der Formgebung von Flugzeug- und Fahrzeugkomponenten auf die Grösse der aerodynamischen Kräfte erklären können. An Beispielen die wesentlichen Probleme und Resultate illustrieren.
Möglichkeiten und Grenzen experimenteller und theoretischer Verfahren zeigen.
InhaltFlugzeugaerodynamik: Atmosphäre; Aerodynamische Kräfte (Auftrieb: Profile, Flügel. Widerstand: Restwiderstand, induzierter Widerstand);Schub (Übersicht der Antriebssysteme, Aerodynamik des Propellers), Einführung in statische Längsstabilität.

Fahrzeugaerodynamik: Grundlagen: Luft- und Massenkräfte, Widerstand , Auftrieb. Aerodynamik und Fahrleistungen. Personenwagen; Nutzfahrzeuge; Rennfahrzeuge
Skript1.) Grundlagen der Flugtechnik
2.) Einführung in die Fahrzeugaerodynamik
LiteraturFlugtechnik:
- Anderson Jr, John D: Introduction to Flight, Mc Graw Hill, Ed 06, 2007; ISBN: 9780073529394
- Mc Cormick, B.W.: Aerodynamics, Aeronautics and Flight Mechanics, John Wiley and Sons, 1979
- Wilcox, David C, Basic Fluid Mechanics. DCW Industries, Inc., 1997
- Schlichting,H. und truckenbrodt, E: Aerodynamik des Flugzeuges (Bd I und II), Springer Verlag, 1960
- Abbott, I. and van Doenhoff, A.: Theory of Wing Sections, McGraw-Hill Book Company, Inc., 1949
- Hoerner, S.F.: Fluid Dynamic Drag, Hoerner Fluid Dynamics, 1951/1965
- Hoerner, S.F.: Fluid Dynamic Lift, Hoerner Fluid Dynamics, 1975
- Perkins, C.D. and Hage, R.E.: Airplane Performance, Stability and Control, John Wiley ans Sons, 1949

Fahrzeugaerodynamik
- Hucho, Wolf-Heinrich: Aerodynamik des Automobils, VDI Verlag, 1994
- Gillespi, Thomas D: Fundamentals of Vehicle Dynamics, SAE, 1992
- Katz Joseph: New Directions in Race Car Aerodynamics, Robert Bentley Publishers, 1995
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.
227-0225-00LLinear System TheoryW6 KP5GM. Colombino
KurzbeschreibungThe class is intended to provide a comprehensive overview of the theory of linear dynamical systems, stability analysis, and their use in control and estimation. The focus is on the mathematics behind the physical properties of these systems and on understanding and constructing proofs of properties of linear control systems.
LernzielStudents should be able to apply the fundamental results in linear system theory to analyze and control linear dynamical systems.
Inhalt- Proof techniques and practices.
- Linear spaces, normed linear spaces and Hilbert spaces.
- Ordinary differential equations, existence and uniqueness of solutions.
- Continuous and discrete-time, time-varying linear systems. Time domain solutions. Time invariant systems treated as a special case.
- Controllability and observability, duality. Time invariant systems treated as a special case.
- Stability and stabilization, observers, state and output feedback, separation principle.
SkriptAvailable on the course Moodle platform.
Voraussetzungen / BesonderesSufficient mathematical maturity, in particular in linear algebra, analysis.
227-0447-00LImage Analysis and Computer Vision Information W6 KP3V + 1UL. Van Gool, E. Konukoglu, F. Yu
KurzbeschreibungLight and perception. Digital image formation. Image enhancement and feature extraction. Unitary transformations. Color and texture. Image segmentation. Motion extraction and tracking. 3D data extraction. Invariant features. Specific object recognition and object class recognition. Deep learning and Convolutional Neural Networks.
LernzielOverview of the most important concepts of image formation, perception and analysis, and Computer Vision. Gaining own experience through practical computer and programming exercises.
InhaltThis course aims at offering a self-contained account of computer vision and its underlying concepts, including the recent use of deep learning.
The first part starts with an overview of existing and emerging applications that need computer vision. It shows that the realm of image processing is no longer restricted to the factory floor, but is entering several fields of our daily life. First the interaction of light with matter is considered. The most important hardware components such as cameras and illumination sources are also discussed. The course then turns to image discretization, necessary to process images by computer.
The next part describes necessary pre-processing steps, that enhance image quality and/or detect specific features. Linear and non-linear filters are introduced for that purpose. The course will continue by analyzing procedures allowing to extract additional types of basic information from multiple images, with motion and 3D shape as two important examples. Finally, approaches for the recognition of specific objects as well as object classes will be discussed and analyzed. A major part at the end is devoted to deep learning and AI-based approaches to image analysis. Its main focus is on object recognition, but also other examples of image processing using deep neural nets are given.
SkriptCourse material Script, computer demonstrations, exercises and problem solutions
Voraussetzungen / BesonderesPrerequisites:
Basic concepts of mathematical analysis and linear algebra. The computer exercises are based on Python and Linux.
The course language is English.
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