MODEL REFERENCE ADAPTIVE CONTROL DESIGN OF DC MOTOR USING FUZZY CONTROLLER

Abstract

The goal of adaptive control is to adjust unknown or changing plant parameters. This is accomplished by either changing parameters in the controller to minimize error, or using plant parameter estimates to change the control signal. Therefore, there are many different approaches to adaptive control such as self-tuning and model reference adaptive control (MRAC). Use of variable speed control to improve DC motor performance and efficiency has become the core of recent developments in industry. Among adaptive control methods the MRAC has earned wide respect since its effectiveness is sufficiently illustrated in real time applications. In this study the idea is for a further perfection to the MRAC method. This is examined when combining the MRAC method with the fuzzy logic control (MRAFC). The choice of the fuzzy logic is based on its main feature; that its logic flow approaches real time situations more than most of the other known algorithms. The idea of perfection is to provide an even more smooth control to the DC motor and to minimize deficiencies of the traditional MRAC method. This study deals with the conventional MRAC and replaces it with MRAFC. The performance of the drive system obtained, formed a set of test conditions with MRAFC. The performance of the drive is tested for load disturbances along with reference model. This study also compares the performance of MRAFC over conventional MRAC. To achieve these objectives the simulation environment is provided in the MATLAB Simulink.