GREY WOLF OPTIMIZATION FOR POSITION CONTROL OF A DIRECT CURRENT MOTOR DRIVEN BY FEEDBACK LINEARIZATION METHOD

Abstract

Several studies dealing with position control of the DC motor have reported issues concerning friction force. This article demonstrates a nonlinear control and optimization strategy for position control of a series servo motor. Once it is empirically verified that the linear model does not adequately reflect the system, the model is upgraded from linear to nonlinear. In the course of the research, the nonlinear feedback linearizing the controller's behavior is examined. A grey wolf metaheuristic optimization algorithm is used to find the coefficients of the controller's gains. In this way, modern methods are applied to take a fresh look at the existing problem. Furthermore, performance for various targeted output signals is compared to show the approach proposed in the study. Also, a compara- tive analysis with whale optimization algorithm is performed. The experimental results acquired on the stated system are shown, and they validate the usage of the nonlinear control, demonstrating the effectiveness of using optimum feedback linearization in electrical machines.