Frequency Domain Identification of

This paper discusses Hammerstein model identifica- tion in frequency domain using the sampled input-output data. By exploring the fundamental frequency and harmonics generated by the unknown nonlinearity, we propose a frequency domain ap- proach and show its convergence for both the linear and nonlinear subsystems in the presence of noise. No a priori knowledge of the structure of the nonlinearity is required and the linear part can be nonparametric.

[1]  D. Westwick,et al.  Separable Least Squares Identification of Nonlinear Hammerstein Models: Application to Stretch Reflex Dynamics , 2001, Annals of Biomedical Engineering.

[2]  B. Ninness,et al.  Asymptotic properties of Hammerstein model estimates , 2000, Proceedings of the 39th IEEE Conference on Decision and Control (Cat. No.00CH37187).

[3]  G. Tolstov Fourier Series , 1962 .

[4]  Wlodzimierz Greblicki,et al.  Continuous-time Hammerstein system identification , 2000, IEEE Trans. Autom. Control..

[5]  E. Brigham,et al.  The fast Fourier transform , 2016, IEEE Spectrum.

[6]  Yves Rolain,et al.  Non-parametric Estimation of the Frequency-response Functions of the Linear Blocks of a Wiener-Hammerstein Model , 1997, Autom..

[7]  Bart De Moor,et al.  Subspace identification of bilinear systems , 1998 .

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

[9]  M. Pawlak On the series expansion approach to the identification of Hammerstein systems , 1991 .

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

[11]  L. Zadeh,et al.  On the Identification Problem , 1956 .

[12]  Er-Wei Bai,et al.  Identification of linear systems with hard input nonlinearities of known structure , 2002, Autom..

[13]  K. Poolla,et al.  New results for Hammerstein system identification , 1995, Proceedings of 1995 34th IEEE Conference on Decision and Control.

[14]  A linear interpolatory algorithm for robust system identification with corrupted measurement data , 1993, IEEE Trans. Autom. Control..

[15]  W. Rugh,et al.  Complete identification of a class of nonlinear systems from steady-state frequency response , 1975 .

[16]  Adam Krzyzak,et al.  On nonparametric estimation of nonlinear dynamic systems by the Fourier series estimate , 1996, Signal Process..

[17]  K. Narendra,et al.  An iterative method for the identification of nonlinear systems using a Hammerstein model , 1966 .

[18]  J. Schoukens,et al.  First estimates of Wiener and Hammerstein systems using multisine excitation , 2001, IMTC 2001. Proceedings of the 18th IEEE Instrumentation and Measurement Technology Conference. Rediscovering Measurement in the Age of Informatics (Cat. No.01CH 37188).

[19]  P. Stoica On the convergence of an iterative algorithm used for Hammerstein system identification , 1981 .

[20]  E. C. Levy Complex-curve fitting , 1959, IRE Transactions on Automatic Control.

[21]  Stephen A. Billings,et al.  Identi cation of a class of nonlinear systems using correlation analysis , 1978 .