Speed Control OF Brushless DC Motor Using Fuzzy controller

Abstract

Brushless DC motors are utilized in numerous industrial systems, serving customers, automotive system and applications. Unlike brushed dc motor, brushless motor use electronic commutation and offer several advantage such as compact size, improved performance and high efficient. The existing control method is unable to control speed of a BLDC motor with rapidly changing and uncertain load condition and also could not adapt to load variation with constant gain value. Thus, the main aim of this thesis is to develop a controller to control the motor on the basis of the parameters varying, rated speed and load variations to ensure a fixed output speed of the Brushless DC motor in the presence of different operating conditions. The fuzzy logic controller is an adjustable controller whose development is gradual and progressive towards becoming an efficient control system. In this thesis fuzzy logic has been used to control the speed of the BLDC motor, which offers accurate and precise control. We can validate effectiveness of the proposed method by develop simulation model in MATLAB-Simulink program. The anticipation of this thesis is that the Fuzzy Logic Controller will outperform PID controller of BLDC motor with respect to settling time (Ts), rise time, and percentage overshoot. In this thesis, the performance of BLDCM with PID control was analyzed and the results were compared with fuzzy control. The fuzzy controller proved to have a better speed response than PID control. In a fuzzy intelligent controller, the plant output is varied for obtaining speed control at operating condition. Using MATLAB/Simulink software, MATLAB models and control system simulation were done on the Brushless DC motor. The findings indicate that the intelligent fuzzy controller is better than the traditional PID controller.