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Subspace Identification and ARX Modeling
KTH, Superseded Departments, Signals, Sensors and Systems.ORCID iD: 0000-0002-6855-5868
2003 (English)In: IFAC Symp on System Identification, 2003Conference paper, Published paper (Refereed)
Abstract [en]

In this paper we present a new identification method that points at the closerelationship between high order ARX modeling and subspace identification. A high orderARX model is utilized to obtain initial estimates of certain Markov parameters. Theseparameters are then used to restructure the data model used for subspace identification tofacilitate the estimation of the state sequence. Based on the estimated state sequence, thesystem parameters are estimated by linear regression. The method is shown to be competitiveto existing subspace methods by a simulation example. The method can also be used,without modification, on closed loop data in contrast to most previously published subspaceidentification methods

Place, publisher, year, edition, pages
2003.
Keyword [en]
multivariable, identification
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:kth:diva-82680OAI: oai:DiVA.org:kth-82680DiVA: diva2:498504
Conference
13'th IFAC Symp on System Identification, Rotterdam, The Netherlands, Aug 27-29 , 2003.
Note
NR 20140805Available from: 2012-02-12 Created: 2012-02-12 Last updated: 2012-02-12Bibliographically approved

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Jansson, Magnus

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