Identification of input-output LPV models

V. Laurain, R. Toth, M. Gilson, H. Garnier

Research output: Chapter in Book/Report/Conference proceedingChapterAcademic

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This chapter presents an overview of the available methods for identifying input-output LPV models both in discrete time and continuous time with the main focus on noise modeling issues. First, a least-squares approach and an instrumental variable method are presented for dealing with LPV-ARX models. Then, a refined instrumental variable approach is discussed to address more sophisticated noise models like Box-Jenkins in the LPV context. This latter approach is also introduced in continuous time and efficient solutions are proposed for both the problem of time-derivative approximation and the issue of continuous-time modeling of the noise.
Original languageEnglish
Title of host publicationLinear parameter-varying system identification: new developments and trends
EditorsP.L. Santos, dos, T.P.A. Perdicoúlis, C. Novara, J. A. Ramos, D. E. Rivera
Place of PublicationSingapore
PublisherWorld Scientific
Number of pages381
ISBN (Print)978-981-4355-44-5
Publication statusPublished - 2011

Publication series

NameAdvanced Series in Electrical and Computer Engineering


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