Model structures for identification of linear parameter-varying (LPV) models

Research output: Chapter in Book/Report/Conference proceedingChapterAcademic

Abstract

Describing nonlinear dynamic systems by linear parameter-varying models has become an attractive tool for control of complex systems with regimedependent (linear) behavior. For the identification of LPV models from experimental data a number of methods has been presented in the literature but a full picture of the underlying identification problem is still missing. In this contribution a solid system theoretic basis for the description of model structures for LPV models is presented, together with a general approach to the LPV identification problem. Use is made of a series expansion approach to LPV modeling, employing orthogonal basis function expansions.
LanguageEnglish
Title of host publicationProceedings of the Workshop on Systems and Control Theory in honor of József Bokor on his 60th Birthday
EditorsK.M. Hangos, L. Nádai
Place of PublicationBudapest
PublisherMTA
Pages15-34
ISBN (Print)978-963-279-039-8
StatePublished - 2009

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Model structures
Identification (control systems)
Large scale systems
Dynamical systems

Cite this

Hof, Van den, P. M. J., Toth, R., & Heuberger, P. S. C. (2009). Model structures for identification of linear parameter-varying (LPV) models. In K. M. Hangos, & L. Nádai (Eds.), Proceedings of the Workshop on Systems and Control Theory in honor of József Bokor on his 60th Birthday (pp. 15-34). Budapest: MTA.
Hof, Van den, P.M.J. ; Toth, R. ; Heuberger, P.S.C./ Model structures for identification of linear parameter-varying (LPV) models. Proceedings of the Workshop on Systems and Control Theory in honor of József Bokor on his 60th Birthday. editor / K.M. Hangos ; L. Nádai. Budapest : MTA, 2009. pp. 15-34
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abstract = "Describing nonlinear dynamic systems by linear parameter-varying models has become an attractive tool for control of complex systems with regimedependent (linear) behavior. For the identification of LPV models from experimental data a number of methods has been presented in the literature but a full picture of the underlying identification problem is still missing. In this contribution a solid system theoretic basis for the description of model structures for LPV models is presented, together with a general approach to the LPV identification problem. Use is made of a series expansion approach to LPV modeling, employing orthogonal basis function expansions.",
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Hof, Van den, PMJ, Toth, R & Heuberger, PSC 2009, Model structures for identification of linear parameter-varying (LPV) models. in KM Hangos & L Nádai (eds), Proceedings of the Workshop on Systems and Control Theory in honor of József Bokor on his 60th Birthday. MTA, Budapest, pp. 15-34.

Model structures for identification of linear parameter-varying (LPV) models. / Hof, Van den, P.M.J.; Toth, R.; Heuberger, P.S.C.

Proceedings of the Workshop on Systems and Control Theory in honor of József Bokor on his 60th Birthday. ed. / K.M. Hangos; L. Nádai. Budapest : MTA, 2009. p. 15-34.

Research output: Chapter in Book/Report/Conference proceedingChapterAcademic

TY - CHAP

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AU - Heuberger,P.S.C.

PY - 2009

Y1 - 2009

N2 - Describing nonlinear dynamic systems by linear parameter-varying models has become an attractive tool for control of complex systems with regimedependent (linear) behavior. For the identification of LPV models from experimental data a number of methods has been presented in the literature but a full picture of the underlying identification problem is still missing. In this contribution a solid system theoretic basis for the description of model structures for LPV models is presented, together with a general approach to the LPV identification problem. Use is made of a series expansion approach to LPV modeling, employing orthogonal basis function expansions.

AB - Describing nonlinear dynamic systems by linear parameter-varying models has become an attractive tool for control of complex systems with regimedependent (linear) behavior. For the identification of LPV models from experimental data a number of methods has been presented in the literature but a full picture of the underlying identification problem is still missing. In this contribution a solid system theoretic basis for the description of model structures for LPV models is presented, together with a general approach to the LPV identification problem. Use is made of a series expansion approach to LPV modeling, employing orthogonal basis function expansions.

M3 - Chapter

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SP - 15

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BT - Proceedings of the Workshop on Systems and Control Theory in honor of József Bokor on his 60th Birthday

PB - MTA

CY - Budapest

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Hof, Van den PMJ, Toth R, Heuberger PSC. Model structures for identification of linear parameter-varying (LPV) models. In Hangos KM, Nádai L, editors, Proceedings of the Workshop on Systems and Control Theory in honor of József Bokor on his 60th Birthday. Budapest: MTA. 2009. p. 15-34.