Subspace Identification and ARX Modeling
2003 (English)In: IFAC Symp on System Identification, 2003Conference paper (Refereed)
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
IdentifiersURN: urn:nbn:se:kth:diva-82680OAI: oai:DiVA.org:kth-82680DiVA: diva2:498504
13'th IFAC Symp on System Identification, Rotterdam, The Netherlands, Aug 27-29 , 2003.
NR 201408052012-02-122012-02-122012-02-12Bibliographically approved