Structure-preserving model reduction

Authors:
Ren-Cang Li;Zhaojun Bai
Affiliations:
Department of Mathematics, University of Kentucky, Lexington, KY;Department of Computer Science and Department of Mathematics, University of California, Davis, CA
Venue:
PARA'04 Proceedings of the 7th international conference on Applied Parallel Computing: state of the Art in Scientific Computing
Year:
2004

Citing 4
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Abstract

A general framework for structure-preserving model reduction by Krylov subspace projection methods is developed. The goal is to preserve any substructures of importance in the matrices L, G, C, B that define the model prescribed by transfer function H(s)=L*(G +sC)−−1B. Many existing structure-preserving model-order reduction methods for linear and second-order dynamical systems can be derived under this general framework.