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A local identification method for linear parameter-varying systems based on interpolation of state-space matrices and least-squares approximation

Tijdschriftbijdrage - Tijdschriftartikel

This paper proposes a novel state-space matrix interpolation technique to generate linear parameter-varying (LPV) models starting from a set of local linear time-invariant (LTI) models estimated at fixed operating conditions. Since the state-space representation of LTI models is unique up to a similarity transformation, the state-space matrices need to be represented in a common state-space form. This is needed to avoid potentially large variations as a function of the scheduling parameters of the state-space matrices to be interpolated due to underlying similarity transformations, which might degrade the accuracy of the interpolation significantly. Underlying linear state coordinate transformations for a set of local LTI models are extracted by the computation of similarity transformation matrices by means of linear least-squares approximations. These matrices are then used to transform the local LTI state-space matrices into a form suitable to achieve accurate interpolation results. The proposed LPV modeling technique is validated by pertinent numerical results.
Tijdschrift: Mechanical Systems and Signal Processing
ISSN: 0888-3270
Volume: 82
Pagina's: 478-489
Jaar van publicatie:2017
Trefwoorden:Interpolation, Linear parameter-varying (LPV) systems, State-space matrices, System identification
CSS-citation score:1
Auteurs:International
Toegankelijkheid:Closed