Title :
Identification methods of Hammerstein nonelinear CARAR systems
Author :
Xiao, Yongsong ; Yue, Na ; Ding, Feng
Author_Institution :
Control Sci. & Eng. Res. Center, Jiangnan Univ., Wuxi, China
Abstract :
A recursive generalized least squares and a generalized stochastic gradient algorithms are developed for Hammerstein nonlinear systems with memoryless nonlinear blocks followed by linear dynamical blocks described by CARAR models (HCARAR models). The basic idea is to replace the unmeasurable noise terms in the information vectors with their estimates and to compute the noise estimates through different methods. The simulation results show the performance of the proposed algorithms.
Keywords :
gradient methods; identification; least squares approximations; nonlinear control systems; recursive estimation; Hammerstein nonlinear CARAR system; generalized stochastic gradient algorithm; identification method; linear dynamical block; memoryless nonlinear block; recursive generalized least square; Computational modeling; Least squares approximation; Least squares methods; Nonlinear control systems; Nonlinear systems; Parameter estimation; Polynomials; Stochastic resonance; Stochastic systems; Vectors; Hammerstein Models; Least Squares; Parameter Estimation; Recursive Identification; Stochastic Gradient;
Conference_Titel :
Control and Decision Conference (CCDC), 2010 Chinese
Conference_Location :
Xuzhou
Print_ISBN :
978-1-4244-5181-4
Electronic_ISBN :
978-1-4244-5182-1
DOI :
10.1109/CCDC.2010.5498591
