Identification of input-output LPV models

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

Research output: Chapter in Book/Report/Conference proceedingChapterAcademic

Abstract

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.
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
Pages95-131
Number of pages381
ISBN (Print)978-981-4355-44-5
DOIs
StatePublished - 2011

Publication series

NameAdvanced Series in Electrical and Computer Engineering
Volume14

Fingerprint

Identification (control systems)
Derivatives

Cite this

Laurain, V., Toth, R., Gilson, M., & Garnier, H. (2011). Identification of input-output LPV models. In P. L. Santos, dos, T. P. A. Perdicoúlis, C. Novara, J. A. Ramos, & D. E. Rivera (Eds.), Linear parameter-varying system identification: new developments and trends (pp. 95-131). (Advanced Series in Electrical and Computer Engineering; Vol. 14). Singapore: World Scientific. DOI: 10.1142/9789814355452_0005
Laurain, V. ; Toth, R. ; Gilson, M. ; Garnier, H./ Identification of input-output LPV models. Linear parameter-varying system identification: new developments and trends. editor / P.L. Santos, dos ; T.P.A. Perdicoúlis ; C. Novara ; J. A. Ramos ; D. E. Rivera. Singapore : World Scientific, 2011. pp. 95-131 (Advanced Series in Electrical and Computer Engineering).
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Laurain, V, Toth, R, Gilson, M & Garnier, H 2011, Identification of input-output LPV models. in PL Santos, dos, TPA Perdicoúlis, C Novara, JA Ramos & DE Rivera (eds), Linear parameter-varying system identification: new developments and trends. Advanced Series in Electrical and Computer Engineering, vol. 14, World Scientific, Singapore, pp. 95-131. DOI: 10.1142/9789814355452_0005

Identification of input-output LPV models. / Laurain, V.; Toth, R.; Gilson, M.; Garnier, H.

Linear parameter-varying system identification: new developments and trends. ed. / P.L. Santos, dos; T.P.A. Perdicoúlis; C. Novara; J. A. Ramos; D. E. Rivera. Singapore : World Scientific, 2011. p. 95-131 (Advanced Series in Electrical and Computer Engineering; Vol. 14).

Research output: Chapter in Book/Report/Conference proceedingChapterAcademic

TY - CHAP

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AB - 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.

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DO - 10.1142/9789814355452_0005

M3 - Chapter

SN - 978-981-4355-44-5

T3 - Advanced Series in Electrical and Computer Engineering

SP - 95

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BT - Linear parameter-varying system identification: new developments and trends

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ER -

Laurain V, Toth R, Gilson M, Garnier H. Identification of input-output LPV models. In Santos, dos PL, Perdicoúlis TPA, Novara C, Ramos JA, Rivera DE, editors, Linear parameter-varying system identification: new developments and trends. Singapore: World Scientific. 2011. p. 95-131. (Advanced Series in Electrical and Computer Engineering). Available from, DOI: 10.1142/9789814355452_0005