Identification of MIMO LPV models based on interpolation
This paper presents SMILE (State-space Model Interpolation of Local Estimates), a new technique to estimate linear parameter varying state-space models for multiple-input multiple-output systems whose dynamics depends on a single varying parameter, called the scheduling parameter. The SMILE techniqu...
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creator | De Caigny, Jan Camino, Juan Swevers, Jan |
description | This paper presents SMILE (State-space Model Interpolation of Local Estimates), a new technique to estimate linear parameter varying state-space models for multiple-input multiple-output systems whose dynamics depends on a single varying parameter, called the scheduling parameter. The SMILE technique is based on the interpolation of linear time-invariant models that are valid for fixed operating conditions of the system, that is, for constant values of the scheduling parameters. The methodology yields affine LPV models that are numerically well-conditioned and therefore suitable for LPV control synthesis procedures. The underlying interpolation technique is formulated as a nonlinear least-squares optimization problem that can be efficiently solved by standard solvers. Application of the proposed methodology to a vibroacoustic setup, whose dynamics are highly sensitive to the ambient temperature, clearly demonstrates the potential of the SMILE technique. © 2008 by the Katholieke Universiteit Leuven Department of Mechanical Engineering All rights reserved. |
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The SMILE technique is based on the interpolation of linear time-invariant models that are valid for fixed operating conditions of the system, that is, for constant values of the scheduling parameters. The methodology yields affine LPV models that are numerically well-conditioned and therefore suitable for LPV control synthesis procedures. The underlying interpolation technique is formulated as a nonlinear least-squares optimization problem that can be efficiently solved by standard solvers. Application of the proposed methodology to a vibroacoustic setup, whose dynamics are highly sensitive to the ambient temperature, clearly demonstrates the potential of the SMILE technique. © 2008 by the Katholieke Universiteit Leuven Department of Mechanical Engineering All rights reserved.</description><identifier>ISBN: 9073802865</identifier><identifier>ISBN: 9789073802865</identifier><language>eng</language><publisher>KATHOLIEKE UNIV LEUVEN, DEPT WERKTUIGKUNDE</publisher><ispartof>Proceedings of the International Conference on Noise and Vibration Engineering, 2008, Vol.5, p.2631-2644</ispartof><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>309,310,315,780,27860</link.rule.ids><linktorsrc>$$Uhttps://lirias.kuleuven.be/handle/123456789/208369$$EView_record_in_KU_Leuven_Association$$FView_record_in_$$GKU_Leuven_Association$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>De Caigny, Jan</creatorcontrib><creatorcontrib>Camino, Juan</creatorcontrib><creatorcontrib>Swevers, Jan</creatorcontrib><title>Identification of MIMO LPV models based on interpolation</title><title>Proceedings of the International Conference on Noise and Vibration Engineering</title><description>This paper presents SMILE (State-space Model Interpolation of Local Estimates), a new technique to estimate linear parameter varying state-space models for multiple-input multiple-output systems whose dynamics depends on a single varying parameter, called the scheduling parameter. 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The SMILE technique is based on the interpolation of linear time-invariant models that are valid for fixed operating conditions of the system, that is, for constant values of the scheduling parameters. The methodology yields affine LPV models that are numerically well-conditioned and therefore suitable for LPV control synthesis procedures. The underlying interpolation technique is formulated as a nonlinear least-squares optimization problem that can be efficiently solved by standard solvers. Application of the proposed methodology to a vibroacoustic setup, whose dynamics are highly sensitive to the ambient temperature, clearly demonstrates the potential of the SMILE technique. © 2008 by the Katholieke Universiteit Leuven Department of Mechanical Engineering All rights reserved.</abstract><pub>KATHOLIEKE UNIV LEUVEN, DEPT WERKTUIGKUNDE</pub><oa>free_for_read</oa></addata></record> |
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title | Identification of MIMO LPV models based on interpolation |
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