Model order reduction by parameter-varying oblique projection

Julian Theis, Peter Seiler, Herbert Werner

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

A method to reduce the dynamic order of linear parameter-varying (LPV) systems in grid representation is developed in this paper. It approximates balancing and truncation by an oblique projection onto a dominant subspace. The approach is novel in its use of a parameter-varying kernel to define the direction of this projection. Parameter-varying state transformations in general lead to parameter rate dependence in the model. The proposed projection avoids this dependence and maintains a consistent state space basis for the reduced-order system. The method is compared with LPV balancing and truncation for a nonlinear mass-spring-damper system. It is shown to yield similar accuracy, while the required computation time is reduced by a factor of almost 100,000.

Original languageEnglish (US)
Title of host publication2016 American Control Conference, ACC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4586-4591
Number of pages6
ISBN (Electronic)9781467386821
DOIs
StatePublished - Jul 28 2016
Event2016 American Control Conference, ACC 2016 - Boston, United States
Duration: Jul 6 2016Jul 8 2016

Publication series

NameProceedings of the American Control Conference
Volume2016-July
ISSN (Print)0743-1619

Other

Other2016 American Control Conference, ACC 2016
Country/TerritoryUnited States
CityBoston
Period7/6/167/8/16

Bibliographical note

Publisher Copyright:
© 2016 American Automatic Control Council (AACC).

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