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)
Abstract
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.
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