System identification of Hammerstein models by using backward shift algorithm

doi:10.1016/j.amc.2021.126620

System identification of Hammerstein models by using backward shift algorithm

2022-01-01

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DOI：10.1016/j.amc.2021.126620

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In this paper, a new identification method for discrete-time Hammerstein systems is proposed. The method is a joint use of discrete Fourier transform, backward shift method, and the least squares method. The frequency responses are obtained with sampled input and output data in the time domain through discrete Fourier transform. It is followed by the backward shift algorithm that was originally developed for estimating poles of linear time-invariant systems. After poles of linear subsystem are estimated, coefficients of linear and nonlinear subsystems are respectively determined by using the least squares (LS) method. The robustness of the backward shift algorithm guarantees the effectiveness of the proposed algorithm. Simulation results show that the poles of linear subsystem are well located. Thus, it is practical to identify discrete Hammerstein systems. (C) 2021 Published by Elsevier Inc.

Keywords:

Nonlinear system

Backward shift

Hammerstein system

System identification

Transfer function

System identification of Hammerstein models by using backward shift algorithm

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