Abstract For Hammerstein-Wiener model with colored process noise, this paper derives an identification approach. The correlation function between input and output data points is derived by using separable signal to realize that the unmeasurable internal variable is replaced by the correlation function of input, and then correlation analysis method is used to estimate the parameters of the output nonlinear part and linear part. Furthermore, a correction term is added to least square estimation to compensate error caused by process noise, and then to derive an error compensation recursive least square method for the observed data from Hammerstein-Wiener model. Therefore, the parameters of the input nonlinear part can be estimated by error compensation method. Finally, the advantages of proposed algorithm are shown by simulation example.


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    Title :

    Identification Approach of Hammerstein-Wiener Model Corrupted by Colored Process Noise


    Contributors:
    Li, Feng (author) / Jia, Li (author) / Xiong, Qi (author)


    Publication date :

    2017-01-01


    Size :

    10 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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