STEPPER MOTOR SYSTEM IDENTIFICATION USING INVERSE DYNAMIC NEURAL MIMO NARX MODEL

Abstract

This paper introduces the novel inverse dynamic intelligent MIMO model which is applied for modeling and identifying the stepper motor dynamic model. Hence the highly nonlinear features of stepper motor system are modeled thoroughly based on the inverse neural NARX model identification process using experimental input-output training data. Consequently the proposed inverse neural NARX MIMO model scheme of the nonlinear stepper motor has been investigated. The results showed that the proposed inverse neural NARX MIMO model trained by the back propogation learning algorithm (BP) yields outstanding performance and perfect accuracy.