Title :
Recursive identification for Wiener-Hammerstein systems using instrumental variable
Author :
Chen Xi ; Fang Hai-Tao
Author_Institution :
Inst. of Syst. Sci., Beijing, China
Abstract :
An identification method is discussed that deals with the Wiener-Hammerstein systems of general nonlinearity. By introducing a suitable instrumental variable a new algorithm is presented to recursively estimate the linear subsystems using stochastic approximation algorithm. The kernel nonparametric method is used to estimate the nonlinear function. The consistent analysis of the method is given under mild condition. A simulation example is provided justifying the proposed method.
Keywords :
approximation theory; linear systems; nonlinear functions; nonparametric statistics; recursive estimation; stochastic processes; stochastic systems; Wiener-Hammerstein systems; consistent analysis; general nonlinearity; identification method; instrumental variable; kernel nonparametric method; linear subsystems; nonlinear function estimation; recursive estimation; recursive identification; stochastic approximation algorithm; Algorithm design and analysis; Approximation algorithms; Equations; Estimation; Instruments; Kernel; Nonlinear systems; Instrumental variable; Recursive estimate; Wiener-Hammerstein systems;
Conference_Titel :
Intelligent Control and Automation (WCICA), 2012 10th World Congress on
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-1397-1
DOI :
10.1109/WCICA.2012.6358393
