Suchergebnis: Katalogdaten im Frühjahrssemester 2020

Rechnergestützte Wissenschaften Master Information
Von den angebotenen Kernfächern müssen mindestens zwei Lerneinheiten erfolgreich abgeschlossen werden.
401-3632-00LComputational StatisticsW8 KP3V + 1UM. H. Maathuis
KurzbeschreibungWe discuss modern statistical methods for data analysis, including methods for data exploration, prediction and inference. We pay attention to algorithmic aspects, theoretical properties and practical considerations. The class is hands-on and methods are applied using the statistical programming language R.
LernzielThe student obtains an overview of modern statistical methods for data analysis, including their algorithmic aspects and theoretical properties. The methods are applied using the statistical programming language R.
Voraussetzungen / BesonderesAt least one semester of (basic) probability and statistics.

Programming experience is helpful but not required.
263-0007-00LAdvanced Systems Lab Information Belegung eingeschränkt - Details anzeigen
Only for master students, otherwise a special permission by the study administration of D-INFK is required.
W8 KP3V + 2U + 2AM. Püschel, C. Zhang
KurzbeschreibungThis course introduces the student to the foundations and state-of-the-art techniques in developing high performance software for mathematical functionality occurring in various fields in computer science. The focus is on optimizing for a single core and includes optimizing for the memory hierarchy, for special instruction sets, and the possible use of automatic performance tuning.
LernzielSoftware performance (i.e., runtime) arises through the complex interaction of algorithm, its implementation, the compiler used, and the microarchitecture the program is run on. The first goal of the course is to provide the student with an understanding of this "vertical" interaction, and hence software performance, for mathematical functionality. The second goal is to teach a systematic strategy how to use this knowledge to write fast software for numerical problems. This strategy will be trained in several homeworks and a semester-long group project.
InhaltThe fast evolution and increasing complexity of computing platforms pose a major challenge for developers of high performance software for engineering, science, and consumer applications: it becomes increasingly harder to harness the available computing power. Straightforward implementations may lose as much as one or two orders of magnitude in performance. On the other hand, creating optimal implementations requires the developer to have an understanding of algorithms, capabilities and limitations of compilers, and the target platform's architecture and microarchitecture.

This interdisciplinary course introduces the student to the foundations and state-of-the-art techniques in high performance mathematical software development using important functionality such as matrix operations, transforms, filters, and others as examples. The course will explain how to optimize for the memory hierarchy, take advantage of special instruction sets, and other details of current processors that require optimization. The concept of automatic performance tuning is introduced. The focus is on optimization for a single core; thus, the course complements others on parallel and distributed computing.

Finally a general strategy for performance analysis and optimization is introduced that the students will apply in group projects that accompany the course.
Voraussetzungen / BesonderesSolid knowledge of the C programming language and matrix algebra.
261-5110-00LOptimization for Data Science Information W8 KP3V + 2U + 2AB. Gärtner, D. Steurer
KurzbeschreibungThis course provides an in-depth theoretical treatment of optimization methods that are particularly relevant in data science.
LernzielUnderstanding the theoretical guarantees (and their limits) of relevant optimization methods used in data science. Learning general paradigms to deal with optimization problems arising in data science.
InhaltThis course provides an in-depth theoretical treatment of optimization methods that are particularly relevant in machine learning and data science.

In the first part of the course, we will first give a brief introduction to convex optimization, with some basic motivating examples from machine learning. Then we will analyse classical and more recent first and second order methods for convex optimization: gradient descent, projected gradient descent, subgradient descent, stochastic gradient descent, Nesterov's accelerated method, Newton's method, and Quasi-Newton methods. The emphasis will be on analysis techniques that occur repeatedly in convergence analyses for various classes of convex functions. We will also discuss some classical and recent theoretical results for nonconvex optimization.

In the second part, we discuss convex programming relaxations as a powerful and versatile paradigm for designing efficient algorithms to solve computational problems arising in data science. We will learn about this paradigm and develop a unified perspective on it through the lens of the sum-of-squares semidefinite programming hierarchy. As applications, we are discussing non-negative matrix factorization, compressed sensing and sparse linear regression, matrix completion and phase retrieval, as well as robust estimation.
Voraussetzungen / BesonderesAs background, we require material taught in the course "252-0209-00L Algorithms, Probability, and Computing". It is not necessary that participants have actually taken the course, but they should be prepared to catch up if necessary.
402-0394-00LTheoretical Cosmology
Studierende der UZH dürfen diese Lerneinheit nicht an der ETH belegen, sondern müssen das entsprechende Modul direkt an der UZH buchen.
W10 KP4V + 2UL. M. Mayer, J. Yoo
KurzbeschreibungThis is the second of a two course series which starts with "General Relativity" and continues in the spring with "Theoretical Astrophysics and Cosmology", where the focus will be on applying general relativity to cosmology as well as developing the modern theory of structure formation in a cold dark matter Universe.
LernzielLearning the fundamentals of modern physical cosmology. This
entails understanding the physical principles behind the description
of the homogeneous Universe on large scales in the first part of the
course, and moving on to the inhomogeneous Universe model where
perturbation theory is used to study the development of structure
through gravitational instability in the second part of the course.
Modern notions of dark matter and dark energy will also be introduced and discussed.
InhaltThe course will cover the following topics:
- Homogeneous cosmology
- Thermal history of the universe, recombination, baryogenesis and nucleosynthesis
- Dark matter and Dark Energy
- Inflation
- Perturbation theory: Relativistic and Newtonian
- Model of structure formation and initial conditions from Inflation
- Cosmic microwave background anisotropies
- Spherical collapse and galaxy formation
- Large scale structure and cosmological probes
LiteraturSuggested textbooks:
H.Mo, F. Van den Bosch, S. White: Galaxy Formation and Evolution
S. Carroll: Space-Time and Geometry: An Introduction to General Relativity
S. Dodelson: Modern Cosmology
Secondary textbooks:
S. Weinberg: Gravitation and Cosmology
V. Mukhanov: Physical Foundations of Cosmology
E. W. Kolb and M. S. Turner: The Early Universe
N. Straumann: General relativity with applications to astrophysics
A. Liddle and D. Lyth: Cosmological Inflation and Large Scale Structure
Voraussetzungen / BesonderesKnowledge of General Relativity is recommended.
701-1216-00LNumerical Modelling of Weather and Climate Information W4 KP3GC. Schär, S. Soerland, J. Vergara Temprado
KurzbeschreibungThe course provides an introduction to weather and climate models. It discusses how these models are built addressing both the dynamical core and the physical parameterizations, and it provides an overview of how these models are used in numerical weather prediction and climate research. As a tutorial, students conduct a term project and build a simple atmospheric model using the language PYTHON.
LernzielAt the end of this course, students understand how weather and climate models are formulated from the governing physical principles, and how they are used for climate and weather prediction purposes.
InhaltThe course provides an introduction into the following themes: numerical methods (finite differences and spectral methods); adiabatic formulation of atmospheric models (vertical coordinates, hydrostatic approximation); parameterization of physical processes (e.g. clouds, convection, boundary layer, radiation); atmospheric data assimilation and weather prediction; predictability (chaos-theory, ensemble methods); climate models (coupled atmospheric, oceanic and biogeochemical models); climate prediction. Hands-on experience with simple models will be acquired in the tutorials.
SkriptSlides and lecture notes will be made available at
LiteraturList of literature will be provided.
Voraussetzungen / BesonderesPrerequisites: to follow this course, you need some basic background in atmospheric science, numerical methods (e.g., "Numerische Methoden in der Umweltphysik", 701-0461-00L) as well as experience in programming. Previous experience with PYTHON is useful but not required.
701-1232-00LRadiation and Climate ChangeW3 KP2GM. Wild
KurzbeschreibungThis lecture focuses on the prominent role of radiation in the energy balance of the Earth and in the context of past and future climate change.
LernzielThe aim of this course is to develop a thorough understanding of the fundamental role of radiation in the context of Earth's energy balance and climate change.
InhaltThe course will cover the following topics:
Basic radiation laws; sun-earth relations; the sun as driver of climate change (faint sun paradox, Milankovic ice age theory, solar cycles); radiative forcings in the atmosphere: aerosol, water vapour, clouds; radiation balance of the Earth (satellite and surface observations, modeling approaches); anthropogenic perturbation of the Earth radiation balance: greenhouse gases and enhanced greenhouse effect, air pollution and global dimming; radiation-induced feedbacks in the climate system (water vapour feedback, snow albedo feedback); climate model scenarios under various radiative forcings.
SkriptSlides will be made available, lecture notes for part of the course
LiteraturAs announced in the course
701-1228-00LCloud Dynamics: Hurricanes Information W4 KP3GU. Lohmann
KurzbeschreibungHurricanes are among the most destructive elements in the atmosphere. This lecture will discuss the physical requirements for their formation, life cycle, damage potential and their relationship to global warming. It also distinguishes hurricanes from thunderstorms and tornadoes.
LernzielAt the end of this course students will be able to distinguish the formation and life cycle mechanisms of tropical cyclones from those of extratropical thunderstorms/cyclones, project how tropical cyclones change in a warmer climate based on their physics and evaluate different tropical cyclone modification ideas.
Inhaltsee course outline at: Link
SkriptSlides will be made available
LiteraturA literature list can be found here: Link
Voraussetzungen / BesonderesAt least one introductory lecture in Atmospheric Science or Instructor's consent. This lecture will build on some concepts of atmospheric dynamics and their governing equations. Thus, mathematical knowledge will be needed to use the equations to understand the material of the course.
701-1270-00LHigh Performance Computing for Weather and ClimateW3 KP3GO. Fuhrer
KurzbeschreibungState-of-the-art weather and climate simulations rely on large and complex software running on supercomputers. This course focuses on programming methods and tools for understanding, developing and optimizing the computational aspects of weather and climate models. Emphasis will be placed on the foundations of parallel computing, practical exercises and emerging trends such as heterogeneous comput
LernzielAfter attending this course, students will be able to:
- understand a broad variety of high performance computing concepts relevant for weather and climate simulations
- work with weather and climate simulation codes that run on large supercomputers
InhaltHPC Overview:
- Why does weather and climate require HPC?
- Today's HPC: Beowulf-style clusters, massively parallel architectures, hybrid computing, accelerators
- Scaling / Parallel efficiency
- Algorithmic motifs in weather and climate

Writing HPC code:
- Data locality and single node efficiency
- Shared memory parallelism with OpenMP
- Distributed memory parallelism with MPI
- GPU computing
- High-level programming and domain-specific languages
Literatur- Introduction to High Performance Computing for Scientists and Engineers, G. Hager and G. Wellein, CRC Press, 2011
- Computer Organization and Design, D.H. Patterson and J.L. Hennessy
- Parallel Computing, A. Grama, A. Gupta, G. Karypis, V. Kumar (Link)
- Parallel Programming in MPI and OpenMP, V. Eijkhout (Link)
Voraussetzungen / Besonderes- fundamentals of numerical analysis and atmospheric modeling
- basic experience in a programming language (C/C++, Fortran, Python, …)
- experience using command line interfaces in *nix environments (e.g., Unix, Linux)
401-5930-00LSeminar in Physics of the Atmosphere for CSEW4 KP2SH. Joos, C. Schär
KurzbeschreibungIn this seminar, the process of writing a scientific proposal will be
introduced. The essential elements of a proposal, including the peer
review process, will be outlined and class exercises will train
scientific writing skills. Knowledge exchange between class
participants is promoted through the preparation of a master thesis
proposal and evaluation of each other's work.
LernzielScientific writing skills
How to effectively write a scientific proposal
InhaltIn this seminar, the process of writing a scientific proposal will be
introduced. The essential elements of a proposal, including the peer
review process, will be outlined and class exercises will train
scientific writing skills. Knowledge exchange between class
participants is promoted through the preparation of a master thesis
proposal and evaluation of each other's work.
529-0474-00LQuantenchemieW6 KP3GS. Knecht, T. Weymuth
KurzbeschreibungEinführung in Konzepte der Elektronenstruktur-Theorie und in die Methoden der numerischen Quantenchemie; begleitende Übungen mit Papier und Bleistift, sowie Anleitungen zu praktischen Berechnungen mit Quantenchemie-Programmen am Computer.
LernzielChemie kann inzwischen vollständig am Computer betrieben werden, eine intellektuelle Leistung, für die 1998 der Nobelpreis an Pople und Kohn verliehen wurde. Diese Vorlesung zeigt, wie das geht. Erarbeitet wird dabei die Vielteilchen-Quantentheorie von Mehrelektronensystemen (Atome und Moleküle) und ihre Implementierung in Computerprogramme. Es soll ein vollständiges Bild der Quantenchemie vermittelt werden, das alles Rüstzeug zur Verfügung stellt, um selbst solche Berechnungen durchführen zu können (sei es begleitend zum Experiment oder als Start in eine Vertiefung dieser Theorie).
InhaltGrundlegende Konzepte der Vielteilchen-Quantenmechanik. Entwicklung der Mehrelektronentheorie für Atome und Moleküle; beginnend bei der harmonischen Näherung für das Kern-Problem und bei der Hartree-Fock-Theorie für das elektronische Problem über Moeller-Plesset-Störungstheorie und Konfigurationswechselwirkung zu Coupled-Cluster und Multikonfigurationsverfahren. Dichtefunktionaltheorie. Verwendung quantenchemischer Software und Problemlösungen mit dem Computer.
SkriptEin Skript zu allen Vorlesungsstunden wird zur Verfügung gestellt (die aufgearbeitete Theorie wird durch praktische Beispiele kontinuierlich begleitet).
F.L. Pilar, Elementary Quantum Chemistry, Dover Publications
I.N. Levine, Quantum Chemistry, Prentice Hall

Hartree-Fock in Basisdarstellung:
A. Szabo and N. Ostlund, Modern Quantum Chemistry: Introduction to Advanced Electronic Structure Theory, McGraw-Hill

Bücher zur Computerchemie:
F. Jensen, Introduction to Computational Chemistry, John Wiley & Sons
C.J. Cramer, Essentials of Computational Chemistry, John Wiley & Sons
Voraussetzungen / BesonderesVoraussetzungen: einführende Vorlesung in Quantenmechanik (z.B. Physikalische Chemie III: Quantenmechanik)
227-0161-00LMolecular and Materials Modelling Information W4 KP2V + 2UD. Passerone, C. Pignedoli
KurzbeschreibungThe course introduces the basic techniques to interpret experiments with contemporary atomistic simulation, including force fields or ab initio based molecular dynamics and Monte Carlo. Structural and electronic properties will be simulated hands-on for realistic systems.
The modern methods of "big data" analysis applied to the screening of chemical structures will be introduced with examples.
LernzielThe ability to select a suitable atomistic approach to model a nanoscale system, and to employ a simulation package to compute quantities providing a theoretically sound explanation of a given experiment. This includes knowledge of empirical force fields and insight in electronic structure theory, in particular density functional theory (DFT). Understanding the advantages of Monte Carlo and molecular dynamics (MD), and how these simulation methods can be used to compute various static and dynamic material properties. Basic understanding on how to simulate different spectroscopies (IR, X-ray, UV/VIS). Performing a basic computational experiment: interpreting the experimental input, choosing theory level and model approximations, performing the calculations, collecting and representing the results, discussing the comparison to the experiment.
Inhalt-Classical force fields in molecular and condensed phase systems
-Methods for finding stationary states in a potential energy surface
-Monte Carlo techniques applied to nanoscience
-Classical molecular dynamics: extracting quantities and relating to experimentally accessible properties
-From molecular orbital theory to quantum chemistry: chemical reactions
-Condensed phase systems: from periodicity to band structure
-Larger scale systems and their electronic properties: density functional theory and its approximations
-Advanced molecular dynamics: Correlation functions and extracting free energies
-The use of Smooth Overlap of Atomic Positions (SOAP) descriptors in the evaluation of the (dis)similarity of crystalline, disordered and molecular compounds
SkriptA script will be made available and complemented by literature references.
LiteraturD. Frenkel and B. Smit, Understanding Molecular Simulations, Academic Press, 2002.

M. P. Allen and D.J. Tildesley, Computer Simulations of Liquids, Oxford University Press 1990.

C. J. Cramer, Essentials of Computational Chemistry. Theories and Models, Wiley 2004

G. L. Miessler, P. J. Fischer, and Donald A. Tarr, Inorganic Chemistry, Pearson 2014.

K. Huang, Statistical Mechanics, Wiley, 1987.

N. W. Ashcroft, N. D. Mermin, Solid State Physics, Saunders College 1976.

E. Kaxiras, Atomic and Electronic Structure of Solids, Cambridge University Press 2010.
327-0613-00LComputer Applications: Finite Elements in Solids and Structures Information
The course will only take place if at least 7 students are enrolled.
W4 KP2V + 2UA. Gusev
KurzbeschreibungEinführung in die Finite-Elemente-Methode für Studenten mit einem allgemeinen Interesse an diesem Gebiet
LernzielEinführung in die Finite-Elemente-Methode für Studenten mit einem allgemeinen Interesse in diesem Gebiet
InhaltEinführung, Energieformulierungen, die Rayleigh-Ritz-Methode, Finite-Elemente der Verschiebungen, Lösungen zu den Finite-Elemente Gleichungen, Lineare Elemente, Konvergenz, Kompatibilität und Vollständigkeit, Finite Elemente höherer Ordnung, Beam- und Frame-Elemente, Plate- und Shell-Elemente, Dynamik und Vibrationen, Verallgemeinerung des Finite-Elemente-Konzeptes (Galerkin-weighted residual and variational approaches)
Literatur- Astley R.J. Finite Elements in Solids and Structures, Chapman & Hill, 1992
- Zienkiewicz O.C., Taylor R.L. The Finite Element Method, 5th ed., vol. 1, Butterworth-Heinemann, 2000
401-5940-00LSeminar in Chemistry for CSEW4 KP2SP. H. Hünenberger
KurzbeschreibungThe student will carry out a literature study on a topic of his or her liking or suggested by the supervisor in the area of computer simulation in chemistry, the results of which are to be presented both orally and in written form.

For more information: Link
Eine der beiden Lerneinheiten
151-0208-00L Berechnungsmethoden der Energie- und Verfahrenstechnik
151-0212-00L Advanced CFD Methods
ist obligatorisch.
151-0208-00LComputational Methods for Flow, Heat and Mass Transfer ProblemsO4 KP4GD. W. Meyer-Massetti
KurzbeschreibungEs werden numerische Methoden zur Lösung von Problemen der Fluiddynamik, Energie- & Verfahrenstechnik dargestellt und anhand von analytischen & numerischen Beispielen illustriert.
LernzielKenntnisse und praktische Erfahrung mit der Anwendung von Diskretisierungs- und Lösungsverfahren für Problem der Fluiddynamik und der Energie- und Verfahrenstechnik
Inhalt- Einleitung mit Anwendungen, Schritte zur numerischen Lösung
- Klassifizierung partieller Differentialgleichungen, Beispiele aus Anwendungen
- Finite Differenzen
- Finite Volumen
- Methoden der gewichteten Residuen, Spektralmethoden, finite Elemente
- Stabilitätsanalyse, Konsistenz, Konvergenz
- Numerische Lösungsverfahren, lineare Löser
Der Stoff wird mit Beispielen aus der Praxis illustriert.
SkriptFolien zur Ergänzung während der Vorlesung werden ausgegeben.
LiteraturReferenzen werden in der Vorlesung angegeben. Notizen in guter Übereinstimmung mit der Vorlesung stehen zur Verfügung.
Voraussetzungen / BesonderesGrundlagen in Fluiddynamik, Thermodynamik und Programmieren (Vorlesung: "Models, Algorithms and Data: Introduction to Computing")
151-0212-00LAdvanced CFD MethodsW4 KP2V + 1UP. Jenny
KurzbeschreibungFundamental and advanced numerical methods used in commercial and open-source CFD codes will be explained. The main focus is on numerical methods for conservation laws with discontinuities, which is relevant for trans- and hypersonic gas dynamics problems, but also CFD of incompressible flows, Direct Simulation Monte Carlo and the Lattice Boltzmann method are explained.
LernzielKnowing what's behind a state-of-the-art CFD code is not only important for developers, but also for users in order to choose the right methods and to achieve meaningful and accurate numerical results. Acquiring this knowledge is the main goal of this course.

Established numerical methods to solve the incompressible and compressible Navier-Stokes equations are explained, whereas the focus lies on finite volume methods for compressible flow simulations. In that context, first the main theory and then numerical schemes related to hyperbolic conservation laws are explained, whereas not only examples from fluid mechanics, but also simpler, yet illustrative ones are considered (e.g. Burgers and traffic flow equations). In addition, two less commonly used yet powerful approaches, i.e., the Direct Simulation Monte Carlo (DSMC) and Lattice Boltzmann methods, are introduced.

For most exercises a C++ code will have to be modified and applied.
Inhalt- Finite-difference vs. finite-element vs. finite-volume methods
- Basic approach to simulate incompressible flows
- Brief introduction to turbulence modeling
- Theory and numerical methods for compressible flow simulations
- Direct Simulation Monte Carlo (DSMC)
- Lattice Boltzmann method
SkriptPart of the course is based on the referenced books. In addition, the participants receive a manuscript and the slides.
Literatur"Computational Fluid Dynamics" by H. K. Versteeg and W. Malalasekera.
"Finite Volume Methods for Hyperbolic Problems" by R. J. Leveque.
Voraussetzungen / BesonderesBasic knowledge in
- fluid dynamics
- numerical mathematics
- programming (programming language is not important, but C++ is of advantage)
151-0110-00LCompressible FlowsW4 KP2V + 1UT. Rösgen
KurzbeschreibungThemen: Instationäre eindimensionale Unterschall- und Überschallströmungen, Akustik, Schallausbreitung, Überschallströmung mit Stössen und Prandtl-Meyer Expansionen, Umströmung von schlanken Körpern, Stossrohre, Reaktionsfronten (Deflagration und Detonation).
Mathematische Werkzeuge: Charakteristikenverfahren, ausgewählte numerische Methoden.
LernzielIllustration der Physik der kompressiblen Strömungen und Üben der mathematischen Methoden anhand einfacher Beispiele.
InhaltDie Kompressibilität im Zusammenspiel mit der Trägheit führen zu Wellen in einem Fluid. So spielt die Kompressibilität bei instationären Vorgängen (Schwingungen in Gasleitungen, Auspuffrohren usw.) eine wichtige Rolle. Auch bei stationären Unterschallströmungen mit hoher Machzahl oder bei Überschallströmungen muss die Kompressibilität berücksichtigt werden (Flugtechnik, Turbomaschinen usw.).
In dem ersten Teil der Vorlesung wird die Wellenausbreitung bei eindimensionalen Unterschall- und Überschallströmungen behandelt. Es werden sowohl Wellen kleiner Amplitude in akustischer Näherung, als auch Wellen grosser Amplitude mit Stossbildung behandelt.

Der zweite Teil befasst sich mit ebenen stationären Überschallströmungen. Schlanke Körper in einer Parallelströmung werden als schwache Störungen der Strömung angesehen und können mit den Methoden der Akustik behandelt werden. Zu der Beschreibung der zweidimensionalen Überschallumströmung beliebiger Körper gehören schräge Verdichtungsstösse, Prandtl -Meyer Expansionen usw.. Unterschiedliche Randbedingungen (Wände usw.) und Wechselwirkungen, Reflexionen werden berücksichtigt.
Skriptnicht verfügbar
LiteraturEine Literaturliste mit Buchempfehlungen wird am Anfang der Vorlesung ausgegeben.
Voraussetzungen / BesonderesVoraussetzungen: Fluiddynamik I und II
401-5950-00LSeminar in Fluid Dynamics for CSE Belegung eingeschränkt - Details anzeigen W4 KP2SP. Jenny, T. Rösgen
KurzbeschreibungEnlarged knowledge and practical abilities in fundamentals and applications of Computational Fluid Dynamics
LernzielEnlarged knowledge and practical abilities in fundamentals and applications of Computational Fluid Dynamics
Voraussetzungen / BesonderesContact Prof. P. Jenny or PD Dr. D. Meyer-Massetti before the beginning of the semester
Systems and Control
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 SystemsW4 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
227-0207-00LNonlinear Systems and Control Information
Voraussetzung: Control Systems (227-0103-00L)
W6 KP4GE. Gallestey Alvarez, P. F. Al Hokayem
KurzbeschreibungIntroduction to the area of nonlinear systems and their control. Familiarization with tools for analysis of nonlinear systems. Discussion of the various nonlinear controller design methods and their applicability to real life problems.
LernzielOn completion of the course, students understand the difference between linear and nonlinear systems, know the mathematical techniques for analysing these systems, and have learnt various methods for designing controllers accounting for their characteristics.

Course puts the student in the position to deploy nonlinear control techniques in real applications. Theory and exercises are combined for better understanding of the virtues and drawbacks present in the different methods.
InhaltVirtually all practical control problems are of nonlinear nature. In some cases application of linear control methods leads to satisfactory controller performance. In many other cases however, only application of nonlinear analysis and control synthesis methods will guarantee achievement of the desired objectives.

During the past decades mature nonlinear controller design methods have been developed and have proven themselves in applications. After an introduction of the basic methods for analysing nonlinear systems, these methods will be introduced together with a critical discussion of their pros and cons. Along the course 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 and mathematical analysis.
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.
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