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A New Subspace Identification Method for Open and Closed Loop Data
KTH, School of Electrical Engineering (EES), Signal Processing.ORCID iD: 0000-0002-6855-5868
2005 (English)In: IFAC Proceedings Volumes (IFAC-PapersOnline): Volume 16, 2005, 2005, 500-505 p.Conference paper (Refereed)
Abstract [en]

Abstract: Subspace methods have emerged as useful tools for the identification of lineartime invariant discrete time systems. Most of the methods have been developed for theopen loop case to avoid difficulties with data correlations due to the feedback. This paperextends some recent ideas for developing subspace methods that can perform well on datacollected both in open and closed loop conditions. Here, a method that aims at minimizingthe prediction errors in several approximate steps is proposed. The steps involve usingconstrained least squares estimation on models with different degrees of structure such asblock-toeplitz, and reduced rank matrices. The statistical estimation performance of themethod is shown to be competitive to existing subspace methods in a simulation example.

Place, publisher, year, edition, pages
2005. 500-505 p.
Keyword [en]
multivariable, identification, Subspace methods
National Category
Control Engineering Signal Processing
URN: urn:nbn:se:kth:diva-82577ScopusID: 2-s2.0-79960746761ISBN: 008045108XISBN: 978-008045108-4OAI: diva2:498381
16th IFAC World Congress, Prague, Czech Republic, Jul. 4-8, 2005

QC 20120219

Available from: 2012-02-12 Created: 2012-02-12 Last updated: 2012-10-01Bibliographically approved

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