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Course on Model Order Reduction

Course on Model 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.

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Course on Model Order Reduction

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  1. Course onModel Order Reduction Eindhoven, April 10-12, 2006

  2. Organized by…. Centre for Analysis, Scientific Computing and Applications

  3. Model Order Reduction? Obtain a compact description of behavior by reducing the complexity of the model, using only the dominant part of the behavior

  4. 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 preserving (to the possible extent) their input-output behavior. system input output

  5. 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.

  6. Synonyms • Model Order Reduction • Reduced Order Modelling • Behavioural Modelling • Dimension Reduction of Large-Scale Systems

  7. Books • P. Benner, V. Mehrmann, D. Sorensen, “Dimension Reduction of Large-Scale Systems” (2005) • A. Antoulas, “Approximation of Large-Scale Dynamical Systems” (2005) • H.A. van der Vorst, W.H.A. Schilders, “Model Order Reduction: Theory and Practice” (to appear)

  8. Links • http://web.mit.edu/mor/ at MIT • 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

  9. 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

  10. Enjoy the course! Jan ter Maten (COMSON) Siep Weiland (PROMATCH) Wil Schilders (CHAMELEON RF)

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