Deterministic system identification using RBF networks

Abstract

This paper presents an artificial intelligence application using a nonconventional mathematical tool: the radial basis function (RBF) networks, aiming to identify the current plant of an induction motor or other nonlinear systems. Here, the objective is to present the RBF response to different nonlinear systems and analyze the obtained results. A RBF network is trained and simulated in order to obtain the dynamical solution with basin of attraction and equilibrium point for known and unknown system and establish a relationship between these dynamical systems and the RBF response. On the basis of several examples, the results indicating the effectiveness of this approach are demonstrated. © 2014 Joilson Batista de Almeida Rego et al.