Title :
LPV models: Identification for gain scheduling control
Author :
Bamieh, B. ; Giarre, L.
Author_Institution :
Mech. & Environ. Eng., Univ. of California, Santa Barbara, Santa Barbara, CA, USA
Abstract :
In this paper the use of discrete-time Linear Parameter Varying (LPV) models for the gain scheduling control and identification methods for non-linear or time-varying system is considered. We report an overview on the existing literature on LPV systems for gain scheduling control and identification. Moreover, assuming that inputs, outputs and the scheduling parameters are measured, and a form of the functional dependence of the coefficients on the parameters is known, we show how the identification problem can be reduced to a linear regression so that a Least Mean Square and Recursive Least Square identification algorithm can be reformulated. Our methodology is applied for the identification of the LPV model of the stall and surge control for compressors of jet engines.
Keywords :
compressors; discrete time systems; gain control; jet engines; least mean squares methods; linear parameter varying systems; nonlinear control systems; regression analysis; time-varying systems; LPV model; compressors; discrete-time model; gain scheduling control; identification method; jet engines; least mean square algorithm; linear parameter varying model; linear regression; nonlinear system; recursive least square identification algorithm; stall control; surge control; time-varying system; Compressors; Least squares approximations; Linear regression; Robustness; Surges; Trajectory; Gain scheduling control; LPV models; identification for nonlinear systems;
Conference_Titel :
Control Conference (ECC), 2001 European
Conference_Location :
Porto
Print_ISBN :
978-3-9524173-6-2