TY  - CHAP
T2  - 16th IFAC Symposium on System Identification
EP  - 1772
N1  - 16th IFAC Symposium on System Identification held in Brussels (Belgium), 11-13 July 2012
ID  - eprints2448
M1  - 16
N2  - 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.
SN  - 978-3-902823-06-9
UR  - http://www.ifac-papersonline.net/Detailed/55021.html
AV  - public
TI  - Input-Output LPV Model identification with guaranteed quadratic stability
KW  - LPV system; quadratic stability; polynomial optimization; convex relaxation
SP  - 1767
A1  - Cerone, Vito
A1  - Piga, Dario
A1  - Regruto, Diego
A1  - Tóth, Roland
PB  - IFAC
Y1  - 2012/07//
ER  -