Using Geno-Iterative Approach to Identify Weiner and Hammerstein Models

Abstract

This paper presents a novel method for identification of the Weiner and Hammerstein models and the model's parameters by the application of genetic algorithm optimization method and an iterative search through a lock up Table. The coefficient values of both linear and nonlinear parts are estimated by the GA while the type of nonlinearity and degree of delay of the linear part are determined by the iterative search through the lock up Table. The simulation results show the effectiveness and ability of the proposed algorithm for identification and realization of the Weiner and Hammerstein models that describe the real system.