Structure preserving order reduction of large scale second order systems

Behnam Salimbahrami, Boris Lohmann

Research output: Contribution to journalConference articlepeer-review

10 Scopus citations

Abstract

In this paper, we propose a new approach for order reduction of large scale second order systems, preserving the specific structure of the second-order type models. A Krylov subspace method is applied to an equivalent state space model, matching the first Markov parameter (which is zero for second order models) and some of the first moments. Then, a procedure is suggested to recover the second order structure.

Original languageEnglish
Pages (from-to)233-238
Number of pages6
JournalIFAC Proceedings Volumes (IFAC-PapersOnline)
Volume37
Issue number11
DOIs
StatePublished - 2004
Externally publishedYes
Event10th IFAC/IFORS/IMACS/IFIP Symposium on Large Scale Systems: Theory and Applications, LSS 2004 - Osaka, Japan
Duration: 26 Jul 200428 Jul 2004

Keywords

  • Large scale systems
  • Markov parameters
  • Model reduction
  • Reduced-order models
  • Second-order systems

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