Parameter identification of Wiener systems with discontinuous nonlinearities

Abstract The paper deals with modeling and parameter identification of Wiener type nonlinear dynamic systems having discontinuous asymmetric piecewise-linear characteristics with preloads and dead zones. Multiple application of a decomposition technique provides a special form of static nonlinearity description. Its incorporation into the Wiener model leads to an input–output equation where all the model parameters are separated and can be estimated iteratively using input–output data and internal variable estimates. More illustrative examples are included to demonstrate the feasibility of the proposed approach.

[1]  W. R. Cluett,et al.  Identification of Wiener-type nonlinear systems in a noisy environment , 1997 .

[2]  Frank Allgöwer,et al.  Nonlinear structure identification of chemical processes , 1997 .

[3]  Baxter F. Womack,et al.  Discrete time adaptive control of linear systems with preload nonlinearity , 1984, Autom..

[4]  J. Voros.  Identification of Nonlinear Dynamic Systems Using Extended Hammerstein and Wiener Models , 1995 .

[5]  Torbjörn Wigren,et al.  Recursive prediction error identification using the nonlinear wiener model , 1993, Autom..

[6]  Jozef Vörös,et al.  Parameter identification of discontinuous hammerstein systems , 1997, Autom..

[7]  Robert Haber.  Nonlinear System Identification : Input-output Modeling Approach , 1999 .

[8]  Jozef Vörös,et al.  Iterative algorithm for parameter identification of Hammerstein systems with two-segment nonlinearities , 1999, IEEE Trans. Autom. Control..

[9]  M. J. Korenberg,et al.  The identification of nonlinear biological systems: Wiener and Hammerstein cascade models , 1986, Biological Cybernetics.

[10]  B. Womack,et al.  Discrete time adaptive control of linear dynamic systems with a two-segment piecewise-linear asymmetric nonlinearity , 1984 .

[11]  J. Vörös.  A Recursive Method of Nonlinear System Identification Using Block-oriented Models , 1988 .

[12]  Yucai Zhu,et al.  Parametric Wiener Model Identification for Control , 1999 .

[13]  Jean-Marc Vesin,et al.  Stochastic gradient identification of polynomial Wiener systems: analysis and application , 2001, IEEE Trans. Signal Process..

[14]  Lennart Ljung,et al.  System Identification: Theory for the User , 1987 .