Title :
Identification of Hammerstein models with general disturbances
Author :
Ying, Xiang ; Lizhen, Huang ; Yongsheng, Xiao ; Jianhong, Wang
Author_Institution :
Sch. of Inf. Eng., Nanchang Hangkong Univerisy, Nanchang, China
Abstract :
The Hammerstein model is a linear dynamic system following some static nonlinearities. These components of this model are estimated through minimizing the error between simulation outputs and measurement outputs in this paper. For the special case of White Gaussian input signals, parameters of Hammerstein models are estimated by the Bussgang´s classic theorem. For the case of input signals of general disturbances, the Maximum Likelihood method is proposed for the estimation of parameters.
Keywords :
control nonlinearities; identification; linear systems; maximum likelihood estimation; signal processing; Hammerstein model; linear dynamic system; maximum likelihood method; parameter estimation; static nonlinearities; white Gaussian input signal; Data models; Equations; Mathematical model; Maximum likelihood estimation; Noise; Noise measurement; Nonlinear systems; Bussgang´s theorem; Hammerstein model; Nonlinear system; System identification;
Conference_Titel :
Electric Information and Control Engineering (ICEICE), 2011 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-8036-4
DOI :
10.1109/ICEICE.2011.5778155