• DocumentCode
    3290306
  • 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
  • fYear
    2011
  • fDate
    15-17 April 2011
  • Firstpage
    458
  • Lastpage
    461
  • 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;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electric Information and Control Engineering (ICEICE), 2011 International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-8036-4
  • Type

    conf

  • DOI
    10.1109/ICEICE.2011.5778155
  • Filename
    5778155