Title :
Identification of Hammerstein model based on wavelet transform
Author :
Li Zhen-Qiang ; Luo Wen-Guang ; Pan Sheng-Hui ; Lin Chuan
Author_Institution :
Dept. of Electron. Inf. & Control Eng., Guangxi Univ. of Technol., Liuzhou, China
Abstract :
In this paper, we propose the method for identification of Hammerstein model using wavelet transform from the noise corrupted data. The nonlinear static memoryless part of Hammerstein model can be represented as a linear combination of the finite function, the following linear part is an ARMAX model. We can estimate the model by means of the wavelet transform and the numerical algorithm for subspace state space system identification method (N4SID). A simulation example illustrates this approach is effective.
Keywords :
autoregressive moving average processes; memoryless systems; nonlinear systems; state-space methods; wavelet transforms; ARMAX model; Hammerstein model; N4SID; finite function; noise corrupted data; nonlinear static memoryless part; numerical algorithm; subspace state space system identification method; wavelet transform; Data models; Discrete wavelet transforms; Electronic mail; Kalman filters; Numerical models; ARMAX Model; Hammerstein Model; Nonlinear System Identification;
Conference_Titel :
Control Conference (CCC), 2011 30th Chinese
Conference_Location :
Yantai
Print_ISBN :
978-1-4577-0677-6
Electronic_ISBN :
1934-1768
