Identification of wiener model with discontinuous nonlinearities using differential evolution

Abstract

This paper deals with the identification of Wiener models with discontinuous nonlinearities. The identification of the Wiener model is formulated as an optimization problem. Differential evolution algorithm, a powerful and robust evolutionary algorithm, is used to search the optimal parameter of the Wiener model such that the error between the output of true model and that of the identified model is minimized. The proposed method can identify the parameters of linear dynamic subsystems and static nonlinear function of the Wiener model simultaneously, and overcome the difficulty of unavailability of the intermediated signal. Two application examples verify that the proposed method can accurately estimate the parameters of the Wiener model even in a low SNR environment.