Search result: Catalogue data in Autumn Semester 2014

Robotics, Systems and Control Master Information
Core Courses
Robot Design, Modelling and Control
NumberTitleTypeECTSHoursLecturers
151-0601-00LTheory of Robotics and MechatronicsW4 credits3GP. Korba, S. Stoeter, B. Nelson
AbstractThis 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. It’s a requirement for the Robotics Vertiefung and for the Masters in Mechatronics and Microsystems.
ObjectiveRobotics 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. This course is a requirement for the Robotics Vertiefung and for the Masters in Mechatronics and Microsystems.
ContentAn 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.
Lecture notesavailable.
Prerequisites / NoticeThe course will be taught in English.
151-0604-00LMicrorobotics Information W4 credits3GB. Nelson
AbstractMicrorobotics 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 students are expected to submit assignments. The course concludes with an end-of-semester examination.
ObjectiveThe 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.
ContentMain 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
Lecture notesThe powerpoint slides presented in the lectures will be made available in hardcopy and as pdf files. Several readings will also be made available electronically.
Prerequisites / NoticeThe lecture will be taught in English.
376-1504-00LPhysical Human Robot Interaction (pHRI) Restricted registration - show details
This course is restricted to 24 students.
W4 credits2V + 2UR. Gassert, O. Lambercy, R. Riener
AbstractThis course focuses on the emerging, interdisciplinary field of physical human-robot interaction, bringing together themes from robotics, real-time control, human factors, haptics, virtual environments, interaction design and other fields to enable the development of human-oriented robotic systems.
ObjectiveThe objective of this course is to give an introduction to the fundamentals of physical human robot interaction, through lectures on the underlying theoretical/mechatronics aspects and application fields, in combination with a hands-on lab tutorial. The course will guide students through the design and evaluation process of such systems.

By the end of this course, you should understand the critical elements in human-robot interactions - both in terms of engineering and human factors - and use these to evaluate and de- sign safe and efficient assistive and rehabilitative robotic systems. Specifically, you should be able to:

1) identify critical human factors in physical human-robot interaction and use these to derive design requirements;
2) compare and select mechatronic components that optimally fulfill the defined design requirements;
3) derive a model of the device dynamics to guide and optimize the selection and integration of selected components
into a functional system;
4) design control hardware and software and implement and
test human-interactive control strategies on the physical
setup;
5) characterize and optimize such systems using both engineering and psychophysical evaluation metrics;
6) investigate and optimize one aspect of the physical setup and convey and defend the gained insights in a technical presentation.
ContentThis course provides an introduction to fundamental aspects of physical human-robot interaction. After an overview of human haptic, visual and auditory sensing, neurophysiology and psychophysics, principles of human-robot interaction systems (kinematics, mechanical transmissions, robot sensors and actuators used in these systems) will be introduced. Throughout the course, students will gain knowledge of interaction control strategies including impedance/admittance and force control, haptic rendering basics and issues in device design for humans such as transparency and stability analysis, safety hardware and procedures. The course is organized into lectures that aim to bring students up to speed with the basics of these systems, readings on classical and current topics in physical human-robot interaction, laboratory sessions and lab visits.
Students will attend periodic laboratory sessions where they will implement the theoretical aspects learned during the lectures. Here the salient features of haptic device design will be identified and theoretical aspects will be implemented in a haptic system based on the haptic paddle (Link), by creating simple dynamic haptic virtual environments and understanding the performance limitations and causes of instabilities (direct/virtual coupling, friction, damping, time delays, sampling rate, sensor quantization, etc.) during rendering of different mechanical properties.
Lecture notesWill be distributed through the document repository before the lectures.
Link
LiteratureAbbott, J. and Okamura, A. (2005). Effects of position quantization and sampling rate on virtual-wall passivity. Robotics, IEEE Transactions on, 21(5):952 - 964.
Adams, R. and Hannaford, B. (1999). Stable haptic interaction with virtual environments. Robotics and Automation, IEEE Transactions on, 15(3):465 -474.
Buerger, S. and Hogan, N. (2007). Complementary stability and loop shaping for improved human ndash;robot interaction. Robotics, IEEE Transactions on, 23(2):232 -244.
Burdea, G. and Brooks, F. (1996). Force and touch feedback for virtual reality. John Wiley & Sons New York NY.
Colgate, J. and Brown, J. (1994). Factors affecting the z-width of a haptic display. In Robotics and Automation, 1994. Proceedings., 1994 IEEE International Conference on, pages 3205 -3210 vol.4.
Diolaiti, N., Niemeyer, G., Barbagli, F., and Salisbury, J. (2006). Stability of haptic rendering: Discretization, quantization, time delay, and coulomb effects. Robotics, IEEE Transactions on, 22(2):256 -268.
Gillespie, R. and Cutkosky, M. (1996). Stable user-specific haptic rendering of the virtual wall. In Proceedings of the ASME International Mechanical Engineering Congress and Exhibition, volume 58, pages 397-406.
Hannaford, B. and Ryu, J.-H. (2002). Time-domain passivity control of haptic interfaces. Robotics and Automation, IEEE Transactions on, 18(1):1 -10.
Hashtrudi-Zaad, K. and Salcudean, S. (2001). Analysis of control architectures for teleoperation systems with impedance/admittance master and slave manipulators. The International Journal of Robotics Research, 20(6):419.
Hayward, V. and Astley, O. (1996). Performance measures for haptic interfaces. In ROBOTICS RESEARCH-INTERNATIONAL SYMPOSIUM-, volume 7, pages 195-206. Citeseer.
Hayward, V. and Maclean, K. (2007). Do it yourself haptics: part i. Robotics Automation Magazine, IEEE, 14(4):88 -104.
Leskovsky, P., Harders, M., and Szeekely, G. (2006). Assessing the fidelity of haptically rendered deformable objects. In Haptic Interfaces for Virtual Environment and Teleoperator Systems, 2006 14th Symposium on, pages 19 - 25.
MacLean, K. and Hayward, V. (2008). Do it yourself haptics: Part ii [tutorial]. Robotics Automation Magazine, IEEE, 15(1):104 -119.
Mahvash, M. and Hayward, V. (2003). Passivity-based high-fidelity haptic rendering of contact. In Robotics and Automation, 2003. Proceedings. ICRA '03. IEEE International Conference on, volume 3, pages 3722 - 3728 vol.3.
Mehling, J., Colgate, J., and Peshkin, M. (2005). Increasing the impedance range of a haptic display by adding electrical damping. In Eurohaptics Conference, 2005 and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems, 2005. World Haptics 2005. First Joint, pages 257 - 262.
Okamura, A., Richard, C., and Cutkosky, M. (2002). Feeling is believing: Using a force-feedback joystick to teach dynamic systems. JOURNAL OF ENGINEERING EDUCATION-WASHINGTON-, 91(3):345-350.
O'Malley, M. and Goldfarb, M. (2004). The effect of virtual surface stiffness on the haptic perception of detail. Mechatronics, IEEE/ASME Transactions on, 9(2):448 -454.
Richard, C. and Cutkosky, M. (2000). The effects of real and computer generated friction on human performance in a targeting task. In Proceedings of the ASME Dynamic Systems and Control Division, volume 69, page 2.
Salisbury, K., Conti, F., and Barbagli, F. (2004). Haptic rendering: Introductory concepts. Computer Graphics and Applications, IEEE, 24(2):24-32.
Weir, D., Colgate, J., and Peshkin, M. (2008). Measuring and increasing z-width with active electrical damping. In Haptic interfaces for virtual environment and teleoperator systems, 2008. haptics 2008. symposium on, pages 169 -175.
Yasrebi, N. and Constantinescu, D. (2008). Extending the z-width of a haptic device using acceleration feedback. Haptics: Perception, Devices and Scenarios, pages 157-162.
Prerequisites / NoticeNotice:
The registration is limited to 24 students
There are 4 credit points for this lecture.
The lecture will be held in English.
The students are expected to have basic control knowledge from previous classes.
Link
151-0623-00LETH Zurich Distinguished Seminar in Robotics, Systems and ControlsW1 credit1SB. Nelson
AbstractThis course consists of a series of seven lectures given by researchers who have distinguished themselves in the area of Robotics, Systems, and Controls.
ObjectiveObtain an overview of various topics in Robotics, Systems, and Controls from leaders in the field. Please see Link for a list of upcoming lectures.
ContentThis 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.
Prerequisites / NoticeStudents 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.
151-0107-20LHigh Performance Computing for Science and Engineering (HPCSE) IW4 credits4GP. Koumoutsakos, M. Troyer
AbstractThis course gives an introduction into algorithms and numerical methods for parallel computing for multi and many-core architectures and for applications from problems in science and engineering.
ObjectiveIntroduction to HPC for scientists and engineers
Fundamental of:
1. Parallel Computing Architectures
2. MultiCores
3. ManyCores
ContentProgramming models and languages:
1. C++ threading (2 weeks)
2. OpenMP (4 weeks)
3. MPI (5 weeks)

Computers and methods:
1. Hardware and architectures
2. Libraries
3. Particles: N-body solvers
4. Fields: PDEs
5. Stochastics: Monte Carlo
Lecture notesLink
Class notes, handouts
Systems Engineering: Design and Optimization of Products and Systems
NumberTitleTypeECTSHoursLecturers
227-0526-00LPower System Analysis Information W6 credits4GG. Andersson
AbstractThe goal of this course is understanding the stationary and dynamic problems in electrical power systems. The course includes the development of stationary models of the electrical network, their mathematical representation and special characteristics and solution methods of large linear and non-linear systems of equations related to electrical power networks.
ObjectiveThe goal of this course is understanding the stationary and dynamic problems in electrical power systems. The course includes the development of stationary models of the electrical network, their mathematical representation and special characteristics and solution methods of large linear and non-linear systems of equations related to electrical power networks.
ContentThe electrical power transmission system, the energy management system, requirements of the electrical power transmission (demand oriented, operationally, economically), network planning and network operation, models of N-port network components (line, cables, shunts, transformers), the p.u. computation, computer oriented network models, linear networks (solution methods - direct, iterative), algorithms for the solution of non-linear sets of equations, derived from the electrical power system (Newton-Raphson), power flow computation (problem definition, solution methods), three phase short-circuit computation, application of power flow algorithms. Introduction to power system stability.
Lecture notesLecture notes. Course is supported by WWW-teaching system.
227-0247-00LPower Electronic Systems IW6 credits4GJ. W. Kolar
AbstractBasics of the switching behavior, gate drive and snubber circuits of power semiconductors are discussed. Soft-switching and resonant DC/DC converters are analyzed in detail and high frequency loss mechanisms of magnetic components are explained. Space vector modulation of three-phase inverters is introduced and the main power components are designed for typical industry applications.
ObjectiveDetailed understanding of the principle of operation and modulation of advanced power electronics converter systems, especially of zero voltage switching and zero current switching non-isolated and isolated DC/DC converter systems and three-phase voltage DC link inverter systems. Furthermore, the course should convey knowledge on the switching frequency related losses of power semiconductors and inductive power components and introduce the concept of space vector calculus which provides a basis for the comprehensive discussion of three-phase PWM converters systems in the lecture Power Electronic Systems II.
ContentBasics of the switching behavior and gate drive circuits of power semiconductor devices and auxiliary circuits for minimizing the switching losses are explained. Furthermore, zero voltage switching, zero current switching, and resonant DC/DC converters are discussed in detail; the operating behavior of isolated full-bridge DC/DC converters is detailed for different secondary side rectifier topologies; high frequency loss mechanisms of magnetic components of converter circuits are explained and approximate calculation methods are presented; the concept of space vector calculus for analyzing three-phase systems is introduced; finally, phase-oriented and space vector modulation of three-phase inverter systems are discussed related to voltage DC link inverter systems and the design of the main power components based on analytical calculations is explained.
Lecture notesLecture notes and associated exercises including correct answers, simulation program for interactive self-learning including visualization/animation features.
Prerequisites / NoticePrerequisites: Introductory course on power electronics.
227-0697-00LIndustrial Process ControlW4 credits3GG. Maier, A. Horch
AbstractIntroduction to process automation and its application in process industry and power generation
ObjectiveKnowledge of process automation and its application in industry and power generation
ContentIntroduction to process automation: system architecture, data handling, communication (fieldbusses), process visualization, engineering, etc.
Analysis and design of open loop control problems: discrete automata, petri-nets, decision tables, drive control and object oriented function group automation philosophy, RT-UML.
Engineering: Application programming in IEC61131-3 (function blocks, sequence control, structured text); Process visualization and operation; engineering integration from sensor, cabling, topology design, function, visualization, diagnosis, to documentation; Industry standards (e.g. OPC, Profibus)
Ergonomic design, safety (IEC61508) and availability, supervision and diagnosis.
Practical examples from process industry, power generation and newspaper production.
Lecture notesSlides are available as .PDF documents, see "Learning materials" (for registered students only)
Prerequisites / NoticePractical examples will be implemented using industry standard programming tools based on IEC61131-3.
151-0623-00LETH Zurich Distinguished Seminar in Robotics, Systems and ControlsW1 credit1SB. Nelson
AbstractThis course consists of a series of seven lectures given by researchers who have distinguished themselves in the area of Robotics, Systems, and Controls.
ObjectiveObtain an overview of various topics in Robotics, Systems, and Controls from leaders in the field. Please see Link for a list of upcoming lectures.
ContentThis 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.
Prerequisites / NoticeStudents 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.
151-0107-20LHigh Performance Computing for Science and Engineering (HPCSE) IW4 credits4GP. Koumoutsakos, M. Troyer
AbstractThis course gives an introduction into algorithms and numerical methods for parallel computing for multi and many-core architectures and for applications from problems in science and engineering.
ObjectiveIntroduction to HPC for scientists and engineers
Fundamental of:
1. Parallel Computing Architectures
2. MultiCores
3. ManyCores
ContentProgramming models and languages:
1. C++ threading (2 weeks)
2. OpenMP (4 weeks)
3. MPI (5 weeks)

Computers and methods:
1. Hardware and architectures
2. Libraries
3. Particles: N-body solvers
4. Fields: PDEs
5. Stochastics: Monte Carlo
Lecture notesLink
Class notes, handouts
Physical Modelling and Simulation
NumberTitleTypeECTSHoursLecturers
151-0851-00LUnmanned Aerial Systems Information Restricted registration - show details W4 credits2V + 1US. Leutenegger, S.  Lynen, K. Rudin, R. Siegwart
AbstractWe will provide an overview on the field of small Unmanned Aerial Systems (UAS). The course addresses design, modeling, control, as well as perception and navigation of unmanned airplanes and rotorcraft.
ObjectiveThe objective of the course is to provide the background knowledge for the design of simple small UAS', as well as to provide the necessary tools to operate them in indoor or outdoor environments applying state-of-the-art navigation and control algorithms.
ContentThe course consists of three parts: first, the basics of aerodynamics and flight mechanics of fixed wing aircraft are treated, along with related design and control concepts. The second part covers different helicopter types, with a focus on quadrotors and the coaxial configuration. Finally, we enter into the field of localization, mapping and navigation both outdoors as well as indoors. As an example of particular importance, we address state estimation involving computer vision. We treat both recursive estimation techniques as well as nonlinear batch-optimization. Case studies on the three main topics provide the link to real applications and to the state of the art in UAS research.
Prerequisites / NoticeThe contents of the following ETH Bachelor lectures or equivalent are assumed to be known: Fluid Dynamics I and II, Mechanics III, Control Systems I and II
636-0007-00LComputational Systems BiologyW6 credits3V + 2UJ. Stelling
AbstractStudy of fundamental concepts, models and computational methods for the analysis of complex biological networks. Topics: Systems approaches in biology, biology and reaction network fundamentals, modeling and simulation approaches (topological, probabilistic, stoichiometric, qualitative, linear / nonlinear ODEs, stochastic), and systems analysis (complexity reduction, stability, identification).
ObjectiveThe aim of this course is to provide an introductory overview of mathematical and computational methods for the modeling, simulation and analysis of biological networks.
ContentBiology has witnessed an unprecedented increase in experimental data and, correspondingly, an increased need for computational methods to analyze this data. The explosion of sequenced genomes, and subsequently, of bioinformatics methods for the storage, analysis and comparison of genetic sequences provides a prominent example. Recently, however, an additional area of research, captured by the label "Systems Biology", focuses on how networks, which are more than the mere sum of their parts' properties, establish biological functions. This is essentially a task of reverse engineering. The aim of this course is to provide an introductory overview of corresponding computational methods for the modeling, simulation and analysis of biological networks. We will start with an introduction into the basic units, functions and design principles that are relevant for biology at the level of individual cells. Making extensive use of example systems, the course will then focus on methods and algorithms that allow for the investigation of biological networks with increasing detail. These include (i) graph theoretical approaches for revealing large-scale network organization, (ii) probabilistic (Bayesian) network representations, (iii) structural network analysis based on reaction stoichiometries, (iv) qualitative methods for dynamic modeling and simulation (Boolean and piece-wise linear approaches), (v) mechanistic modeling using ordinary differential equations (ODEs) and finally (vi) stochastic simulation methods.
LiteratureU. Alon, An introduction to systems biology. Chapman & Hall / CRC, 2006.

Z. Szallasi et al. (eds.), System modeling in cellular biology. MIT Press, 2006.
151-0623-00LETH Zurich Distinguished Seminar in Robotics, Systems and ControlsW1 credit1SB. Nelson
AbstractThis course consists of a series of seven lectures given by researchers who have distinguished themselves in the area of Robotics, Systems, and Controls.
ObjectiveObtain an overview of various topics in Robotics, Systems, and Controls from leaders in the field. Please see Link for a list of upcoming lectures.
ContentThis 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.
Prerequisites / NoticeStudents 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.
151-0107-20LHigh Performance Computing for Science and Engineering (HPCSE) IW4 credits4GP. Koumoutsakos, M. Troyer
AbstractThis course gives an introduction into algorithms and numerical methods for parallel computing for multi and many-core architectures and for applications from problems in science and engineering.
ObjectiveIntroduction to HPC for scientists and engineers
Fundamental of:
1. Parallel Computing Architectures
2. MultiCores
3. ManyCores
ContentProgramming models and languages:
1. C++ threading (2 weeks)
2. OpenMP (4 weeks)
3. MPI (5 weeks)

Computers and methods:
1. Hardware and architectures
2. Libraries
3. Particles: N-body solvers
4. Fields: PDEs
5. Stochastics: Monte Carlo
Lecture notesLink
Class notes, handouts
Optimization and Control
NumberTitleTypeECTSHoursLecturers
151-0563-01LDynamic Programming and Optimal Control Information W4 credits3GR. D'Andrea
AbstractIntroduction to Dynamic Programming and Optimal Control.
ObjectiveCovers the fundamental concepts of Dynamic Programming & Optimal Control.
ContentDynamic Programming Algorithm; Deterministic Systems and Shortest Path Problems; Infinite Horizon Problems, Bellman Equation; Deterministic Continuous-Time Optimal Control.
LiteratureDynamic Programming and Optimal Control by Dimitri P. Bertsekas, Vol. I, 3rd edition, 2005, 558 pages, hardcover.
Prerequisites / NoticeRequirements: Knowledge of advanced calculus, introductory probability theory, and matrix-vector algebra.
227-0225-00LLinear System TheoryW6 credits5GJ. Lygeros
AbstractThe class is intended to provide a comprehensive overview of the theory of linear dynamical systems, their use in control, filtering, and estimation and their applications to areas ranging from avionics to systems biology.
ObjectiveBy the end of the class students should be comfortable with the fundamental results in linear system theory and the mathematical tools used to derive them.
Content- Rings, fields and linear spaces, normed linear spaces and inner product 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, canonical forms, Kalman decomposition. Time invariant systems treated as a special case.
- Stability and stabilization, observers, state and output feedback, separation principle.
- Realization theory.
Lecture notesF.M. Callier and C.A. Desoer, "Linear System Theory", Springer-Verlag, 1991.
Prerequisites / NoticePrerequisites: Control systems (227-0216-00 or equivalent) and sufficient mathematical maturity.
227-0103-00LControl Systems Information W6 credits2V + 2UM. Morari
AbstractStudy of concepts and methods for the mathematical description and analysis of dynamical systems. The concept of feedback. Design of control systems for single input - single output and multivariable systems.
ObjectiveStudy of concepts and methods for the mathematical description and analysis of dynamical systems. The concept of feedback. Design of control systems for single input - single output and multivariable systems.
ContentProcess automation, concept of control. Modelling of dynamical systems - examples, state space description, linearisation, analytical/numerical solution. Laplace transform, system response for first and second order systems - effect of additional poles and zeros. Closed-loop control - idea of feedback. PID control, Ziegler - Nichols tuning. Stability, Routh-Hurwitz criterion, root locus, frequency response, Bode diagram, Bode gain/phase relationship, controller design via "loop shaping", Nyquist criterion. Feedforward compensation, cascade control. Multivariable systems (transfer matrix, state space representation), multi-loop control, problem of coupling, Relative Gain Array, decoupling, sensitivity to model uncertainty. State space representation (modal description, controllability, control canonical form, observer canonical form), state feedback, pole placement - choice of poles. Observer, observability, duality, separation principle. LQ Regulator, optimal state estimation.
LiteratureG.F. Franklin, J.D. Powell, A. Emami-Naeini. Feedback Control of Dynamic Systems. 6th edition, Prentice Hall, Version 2009, Reading, ISBN 978-0-1350-150-9.Softcover student's edition ca. CHF 110.-. (Spring 2013)
Prerequisites / NoticePrerequisites: Signal and Systems Theory II.

MATLAB is used for system analysis and simulation.
227-0920-00LSeminar in Systems and ControlZ0 credits1SM. Morari, R. D'Andrea, L. Guzzella, J. Lygeros, R. Smith
AbstractCurrent topics in Systems and Control presented mostly by external speakers from academia and industry
Objectivesee above
151-0623-00LETH Zurich Distinguished Seminar in Robotics, Systems and ControlsW1 credit1SB. Nelson
AbstractThis course consists of a series of seven lectures given by researchers who have distinguished themselves in the area of Robotics, Systems, and Controls.
ObjectiveObtain an overview of various topics in Robotics, Systems, and Controls from leaders in the field. Please see Link for a list of upcoming lectures.
ContentThis 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.
Prerequisites / NoticeStudents 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.
227-0689-00LSystem IdentificationW4 credits2V + 1UR. Smith
AbstractTheory and techniques for the identification of dynamic models from experimentally obtained system input-output data.
ObjectiveTo provide a series of practical techniques for the development of dynamical models from experimental data, with the emphasis being on the development of models suitable for feedback control design purposes. To provide sufficient theory to enable the practitioner to understand the trade-offs between model accuracy, data quality and data quantity.
ContentIntroduction to modeling: Black-box and grey-box models; Parametric and non-parametric models; ARX, ARMAX (etc.) models.

Predictive, open-loop, black-box identification methods. Time and frequency domain methods. Subspace identification methods.

Optimal experimental design, Cramer-Rao bounds, input signal design.

Parametric identification methods. On-line and batch approaches.

Closed-loop identification strategies. Trade-off between controller performance and information available for identification.
Literature"System Identification; Theory for the User" Lennart Ljung, Prentice Hall (2nd Ed), 1999.

"Dynamic system identification: Experimental design and data analysis", GC Goodwin and RL Payne, Academic Press, 1977.
Prerequisites / NoticeControl systems (227-0216-00L) or equivalent.
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