Identification of approximative nonlinear state-space models by subspace methods

Andreas Schrempf, Vincent Verdult

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

2 Citations (Scopus)

Abstract

A subspace identification algorithm for state-affine state-space systems which allows to approximate nonlinear systems arbitrarily well is derived. The proposed algorithm depends on an approximation step where a detailed approximation error analysis is provided. A special case is presented in which this approximation error vanishes. To tackle higher-order systems and ill-posed problems a regularized kernel method is proposed. The algorithm is evaluated by a simulation study.

Original languageEnglish
Title of host publicationProceedings of the 16th IFAC World Congress, IFAC 2005
PublisherIFAC Secretariat
Pages934-939
Number of pages6
ISBN (Print)008045108X, 9780080451084
DOIs
Publication statusPublished - 2005
Event16 th IFAC World-Congress - Prag, Czech Republic
Duration: 4 Jul 20058 Jul 2005

Publication series

NameIFAC Proceedings Volumes (IFAC-PapersOnline)
Volume16
ISSN (Print)1474-6670

Conference

Conference16 th IFAC World-Congress
CountryCzech Republic
CityPrag
Period04.07.200508.07.2005

Keywords

  • State-affine systems
  • Subspace identification

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