Analysis of Regenerative Braking In Brushless Dc Motor Drive Using Adaptive Neuro Based Fuzzy Inference System

The electronically commutated Brushless DC motors are widely used in many industrial applications which increase the need for design of efficient control strategy for these motors. This paper deals with the efficient control mechanisms for these drives using meaningful fuzzy sets and rules. The proposed system includes Brushless DC motor control utilizing the PID control, and improved performance via adaptive neuro based fuzzy control. A simplified current controlled modulation technique for BLDC motor is presented so that one can evaluate the performance of the BLDC motor with PWM Control scheme and effective regenerative braking system has been implemented which has the ability to recover energy An adaptive neuro fuzzy inference system is developed using MATLAB. Simulation results shows that ANFIS reaches to the target faster and overcomes the complexity of the problem.