Ulrike Baur, Christopher Beattie, Peter Benner, Serkan Gugercin

Interpolatory Projection Methods for Parameterized Model Reduction

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Kurzfassung in Englisch

We provide a unifying projection-based framework for structure-preserving interpolatory model reduction of parameterized linear dynamical systems, i.e., systems having a structured dependence on parameters that we wish to retain in the reduced-order model. The parameter dependence may be linear or nonlinear and is retained in the reduced-order model. Moreover, we are able to give conditions under which the gradient and Hessian of the system response with respect to the system parameters is matched in the reduced-order model. We provide a systematic approach built on established interpolatory $\mathcal{H}_2$ optimal model reduction methods that will produce parameterized reduced-order models having high fidelity throughout a parameter range of interest. For single input/single output systems with parameters in the input/output maps, we provide reduced-order models that are \emph{optimal} with respect to an $\mathcal{H}_2\otimes\mathcal{L}_2$ joint error measure. The capabilities of these approaches are illustrated by several numerical examples from technical applications.

weitere Metadaten

Titel der Schriftenreihe
(Englisch)
Chemnitz Scientific Computing Preprints ; 09-08
Schlagwörter
linear dynamical systems
Schlagwörter
parameterized model reduction
Schlagwörter
rational Krylov
SWD SchlagworteInterpolation
SWD SchlagworteOrdnungsreduktion
DDC Klassifikation510
Institution(en) 
HochschuleTU Chemnitz
FakultätFakultät für Mathematik
DokumententypPreprint
SpracheEnglisch
Veröffentlichungsdatum (online)05.01.2010
persistente URNurn:nbn:de:bsz:ch1-201000011
ISSN1864-0087
Externe Referenzhttp://www.tu-chemnitz.de/mathematik/csc/preprints.php

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