Order reduction of large scale second-order systems using Krylov subspace methods

Behnam Salimbahrami, Boris Lohmann

Research output: Contribution to journalArticlepeer-review

162 Scopus citations

Abstract

In order reduction of large-scale linear time invariant systems, Krylov subspace methods based on moment matching are among the best choices today. However, in many technical fields, models typically consist of sets of second-order differential equations, and Krylov subspace methods cannot directly be applied. Two methods for solving this problem are presented in this paper: (1) an approach by Su and Craig is generalized and the number of matching moments is increased; (2) a new approach via first-order models is presented, resulting in an even higher number of matching moments. Both solutions preserve the specific structure of the second-order type model.

Original languageEnglish
Pages (from-to)385-405
Number of pages21
JournalLinear Algebra and Its Applications
Volume415
Issue number2-3
DOIs
StatePublished - 1 Jun 2006

Keywords

  • Large scale systems
  • Moment matching
  • Order reduction
  • Second-order Krylov subspace
  • Second-order systems

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