Identification for nonlinear systems by the automatic choosing function and the genetic algorithm

This paper deals with an identification method of nonlinear systems based on the automatic choosing function (ACF). A full data region is divided into some subdomains and the unknown nonlinear function to be estimated is approximately described by a linear equation on each subdomain. These linear equations are united into a single one by the ACF smoothly, and thus the resulting model becomes linear in the parameters. Hence these parameters are easily evaluated by the linear least-squares method. Besides the subdomains and the ACF are properly determined by the genetic algorithm.