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Learn about Model Order Reduction (MOR) which reduces complexity while preserving behavior of dynamical systems. Automatic reduction process, system properties preservation, good approximation, and parametrized models creation among goals. Various methods discussed with hands-on experience.
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Course onModel Order Reduction Eindhoven, April 10-12, 2006
Organized by…. Centre for Analysis, Scientific Computing and Applications
Model Order Reduction? Obtain a compact description of behavior by reducing the complexity of the model, using only the dominant part of the behavior
Model Order Reduction? Model Order Reduction (MOR) is a branch of systems and control theory, which studies properties of dynamical systems in application for reducing their complexity, while preservingtheir input-output behavior. system input output
Goals and problems of Model Order Reduction • To make a reduction process automatic (the algorithm doesn't know anything about the nature of underlying system) • Sometimes we need to preserve some system properties, such as passivity, stability, etc. • To ensure good approximation of the original system by the reduced system in various aspects • Maybe we may vary some parameter of a system (i.e. length of transmission line). We need to be able to create parametrized reduced models. • Since non-reduced models may have millions of unknowns, the algorithm must be efficient.
Synonyms • Model Order Reduction • Reduced Order Modelling • Behavioral Modelling • Dimension Reduction of Large-Scale Systems • ……………
Books • P. Benner, V. Mehrmann, D. Sorensen, “Dimension Reduction of Large-Scale Systems” (2005) • A. Antoulas, “Approximation of Large-Scale Dynamical Systems” (2005) • B. N. Datta, “Numerical Methods for Linear Control systems“ (2004) • G. Obinata, B. D. O. Anderson, “Model Reduction for Control System Design” (2004) • Z. Q. Qu, “Model Order Reduction Techniques with Applications in Finite Element Analysis” (2005) • H.A. van der Vorst, W.H.A. Schilders, “Model Order Reduction: Theory and Practice” (to appear)
Websites • http://www.lc.leidenuniv.nl/lc/web/2005/160/info.php3?wsid=160 (Workshop “Model Order Reduction, Coupled Problems and Optimization”) • http://web.mit.edu/mor/ (Model Order Reduction website at MIT) • http://www.imtek.de/simulation/index.php?page=http://www.imtek.uni-freiburg.de/simulation/benchmark/ (Oberwolfach Model Reduction Benchmark Collection)
More links • Model order reduction page at Institut für Automatisierungstechnik, University of Bremen. • A very big collection of control-related aricles and theses of the Control Group at the University of Cambridge, UK. • Collection of the Model Order Reduction benchmarks for linear and nonlinear problems at the University of Freiburg, Germany. • Another benchmark collection for model reduction from the Niconet web site. • Course material for "Dynamic systems and control" (6.241) course at MIT; essential for understanding dynamic systems theory. • ……and many others
This course • Will provide a thorough introduction to Model Order Reduction • Starts with Basic Concepts in numerical linear algebra and systems&control • Treats the linear case extensively, demonstrating different methods (Krylov based, Gramian based, POD) • Discusses current research (nonlinear MOR, parametrized MOR) • Several applications will be shown • And hands-on experience with a variety of methods and software tools
Enjoy the course! Jan ter Maten (COMSON) Siep Weiland (PROMATCH) Wil Schilders (CHAMELEON RF)