relation: http://eprints.imtlucca.it/2448/
title: Input-Output LPV Model identification with guaranteed quadratic stability
creator: Cerone, Vito
creator: Piga, Dario
creator: Regruto, Diego
creator: Tóth, Roland
subject: QA75 Electronic computers. Computer science
description: The problem of identifying linear parameter-varying (LPV) systems, a-priori known to be quadratically stable, is considered in the paper using an input-output model structure. To solve this problem, a novel constrained optimization-based algorithm is proposed which guarantees quadratic stability of the identified model. It is shown that this estimation objective corresponds to a nonconvex optimization problem, defined by a set of polynomial matrix inequalities (PMI), whose optimal solution can be approximated by means of suitable convex semidefinite relaxations. Applicability of such relaxation-based estimation approach in the presence of either stochastic or deterministic bounded noise is discussed. A simulation example is also given to demonstrate the effectiveness of the resulting identification method.
publisher: IFAC
date: 2012-07
type: Book Section
type: PeerReviewed
format: application/pdf
language: en
identifier: http://eprints.imtlucca.it/2448/1/IFAC2012PreprintPiga.pdf
identifier:   Cerone, Vito and Piga, Dario and Regruto, Diego and Tóth, Roland  Input-Output LPV Model identification with guaranteed quadratic stability.   In:  16th IFAC Symposium on System Identification.   IFAC, pp. 1767-1772.  ISBN 978-3-902823-06-9      (2012)  
relation: http://www.ifac-papersonline.net/Detailed/55021.html
relation: 10.3182/20120711-3-BE-2027.00242