SPEED CONTROL OF DC MOTOR UNDER VARIOUS LOADING CONDITIONS

Abstract

Brush-less DC motor have been widely used as motor motion recently, because Brush-less DC motor has advantages than other motors, such as the efficiency is better 13% than induction motor, the volume is smaller 40% than conventional DC motor[19]. The other advantages, caused no brush so they require little or no maintenance, they generate less acoustic and electrical noise than conventional DC motor, they can be used in hazardous operation environments (with flammable products)[20]. Fuzzy logic and Neural Network based controller is recently getting increasing emphasis in process control applications for their ease of adaptation to new control parameters. This desertion presents the performance comparison of PID Controller and Adaptive Neuro-Fuzzy Logic controller to control speed of a DC motor and Brush-less DC motor when subjected to various loading condition as well as parameter change which happens over a time. To control high-speed motor, a high control frequency is required and also it is difficult to achieve high performance with a conventional controller. The fuzzy control is used to linearize the Torque-speed characteristics of Motor at various loading pattern as well as parameter variation and Neural Network gives easy adaptation to new control parameters. A MATLAB/SIMULINK model of DC motor and BLDC motor speed control using PID and Adaptive Neuro-Fuzzy technique is compared.