An LPV identification framework based on orthonormal basis functions

R. Toth; P.S.C. Heuberger; P.M.J. Hof, Van den

doi:10.3182/20090706-3-FR-2004.00221

An LPV identification framework based on orthonormal basis functions

R. Toth, P.S.C. Heuberger, P.M.J. Hof, Van den

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

12 Citations (Scopus)

148 Downloads (Pure)

Abstract

Describing nonlinear dynamic systems by Linear Parameter-Varying (LPV) models has become an attractive tool for control of complicated systems with regime-dependent (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 systems is presented, together with a general approach to the LPV identification problem. Use is made of a series-expansion approach, employing orthogonal basis functions.

Original language	English
Title of host publication	Proceedings of the 15th IFAC Symposium on System Identification (SYSID 2009) 6-8 July 2009, Saint-Malo, France
Place of Publication	Oxford
Publisher	Pergamon
Pages	1328-1333
ISBN (Print)	978-3-902661-47-0
DOIs	https://doi.org/10.3182/20090706-3-FR-2004.00221
Publication status	Published - 2009
Event	15th IFAC Symposium on System Identification (SYSID 2009) - Saint-Malo, France Duration: 6 Jul 2009 → 8 Jul 2009 Conference number: 15 http://www.sysid2009.org/

Conference

Conference	15th IFAC Symposium on System Identification (SYSID 2009)
Abbreviated title	SYSID 2009
Country/Territory	France
City	Saint-Malo
Period	6/07/09 → 8/07/09
Internet address	http://www.sysid2009.org/

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10.3182/20090706-3-FR-2004.00221

1179248287176041Final author version , 178 KB

Cite this

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title = "An LPV identification framework based on orthonormal basis functions",

abstract = "Describing nonlinear dynamic systems by Linear Parameter-Varying (LPV) models has become an attractive tool for control of complicated systems with regime-dependent (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 systems is presented, together with a general approach to the LPV identification problem. Use is made of a series-expansion approach, employing orthogonal basis functions.",

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year = "2009",

doi = "10.3182/20090706-3-FR-2004.00221",

language = "English",

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pages = "1328--1333",

booktitle = "Proceedings of the 15th IFAC Symposium on System Identification (SYSID 2009) 6-8 July 2009, Saint-Malo, France",

publisher = "Pergamon",

note = "15th IFAC Symposium on System Identification (SYSID 2009), SYSID 2009 ; Conference date: 06-07-2009 Through 08-07-2009",

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Toth, R, Heuberger, PSC & Hof, Van den, PMJ 2009, An LPV identification framework based on orthonormal basis functions. in Proceedings of the 15th IFAC Symposium on System Identification (SYSID 2009) 6-8 July 2009, Saint-Malo, France. Pergamon, Oxford, pp. 1328-1333, 15th IFAC Symposium on System Identification (SYSID 2009), Saint-Malo, France, 6/07/09. https://doi.org/10.3182/20090706-3-FR-2004.00221

An LPV identification framework based on orthonormal basis functions. / Toth, R.; Heuberger, P.S.C.; Hof, Van den, P.M.J.
Proceedings of the 15th IFAC Symposium on System Identification (SYSID 2009) 6-8 July 2009, Saint-Malo, France. Oxford: Pergamon, 2009. p. 1328-1333.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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AU - Heuberger, P.S.C.

AU - Hof, Van den, P.M.J.

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PY - 2009

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N2 - Describing nonlinear dynamic systems by Linear Parameter-Varying (LPV) models has become an attractive tool for control of complicated systems with regime-dependent (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 systems is presented, together with a general approach to the LPV identification problem. Use is made of a series-expansion approach, employing orthogonal basis functions.

AB - Describing nonlinear dynamic systems by Linear Parameter-Varying (LPV) models has become an attractive tool for control of complicated systems with regime-dependent (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 systems is presented, together with a general approach to the LPV identification problem. Use is made of a series-expansion approach, employing orthogonal basis functions.

U2 - 10.3182/20090706-3-FR-2004.00221

DO - 10.3182/20090706-3-FR-2004.00221

M3 - Conference contribution

SN - 978-3-902661-47-0

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EP - 1333

BT - Proceedings of the 15th IFAC Symposium on System Identification (SYSID 2009) 6-8 July 2009, Saint-Malo, France

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CY - Oxford

T2 - 15th IFAC Symposium on System Identification (SYSID 2009)

Y2 - 6 July 2009 through 8 July 2009

ER -

An LPV identification framework based on orthonormal basis functions

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