Parametric model order reduction using pseudoinverses for the matrix interpolation of differently sized reduced models

Matthias Geuss, Heiko K.F. Panzer, Ivor D. Clifford, Boris Lohmann

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

This paper deals with a framework of model order reduction for high-order parametric, linear systems. A set of low-order nonparametric systems with different reduced orders is computed for sample points. Then, two approaches are presented applying pseudoinverses for the introduction of generalized coordinates. Finally, a reduced system for a new parameter value is obtained by interpolating differently sized system matrices. The paper extends current methods to the general case where the local systems have different reduced orders.

Original languageEnglish
Title of host publication19th IFAC World Congress IFAC 2014, Proceedings
EditorsEdward Boje, Xiaohua Xia
PublisherIFAC Secretariat
Pages9468-9473
Number of pages6
ISBN (Electronic)9783902823625
DOIs
StatePublished - 2014
Event19th IFAC World Congress on International Federation of Automatic Control, IFAC 2014 - Cape Town, South Africa
Duration: 24 Aug 201429 Aug 2014

Publication series

NameIFAC Proceedings Volumes (IFAC-PapersOnline)
Volume19
ISSN (Print)1474-6670

Conference

Conference19th IFAC World Congress on International Federation of Automatic Control, IFAC 2014
Country/TerritorySouth Africa
CityCape Town
Period24/08/1429/08/14

Keywords

  • Large-scale systems
  • Model reduction
  • Modeling
  • Parameter-dependent systems

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