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Model Reduction of Time-Varying Systems

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Dimension Reduction of Large-Scale Systems

Part of the book series: Lecture Notes in Computational Science and Engineering ((LNCSE,volume 45))

Summary

This paper presents new recursive projection techniques to compute reduced order models of time-varying linear systems. The methods produce a low rank approximation of the Gramians or of the Hankel map of the system and are mainly based on matrix operations that can exploit sparsity of the model. We show the practical relevance of our results with a few benchmark examples.

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Author information

Authors and Affiliations

  1. School of Computational Science, Florida State University, Tallahassee, USA

    Younes Chahlaoui

  2. CESAME, Université catholique de Louvain, Louvain-la-Neuve, Belgium

    Paul Van Dooren

Authors
  1. Younes Chahlaoui
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  2. Paul Van Dooren
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Editor information

Editors and Affiliations

  1. Fakultät für Mathematik, Technische Universität Chemnitz, 09107, Chemnitz, Germany

    Peter Benner

  2. Department of Computational and Applied Mathematics, Rice University, Main Street 6100, 77005-1892, Houston, TX, USA

    Danny C. Sorensen

  3. Institut für Mathematik, Technische Universität Berlin, Straße des 17. Juni 136, 10623, Berlin, Germany

    Volker Mehrmann

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© 2005 Springer-Verlag Berlin Heidelberg

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Chahlaoui, Y., Van Dooren, P. (2005). Model Reduction of Time-Varying Systems. In: Benner, P., Sorensen, D.C., Mehrmann, V. (eds) Dimension Reduction of Large-Scale Systems. Lecture Notes in Computational Science and Engineering, vol 45. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-27909-1_5

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