Direct torque control of brushless DC motor drives based on ANFIS controller with fuzzy supervisory learning

This paper presents a direct torque control technique for brushless DC motors with non-sinusoidal back electromotive force. Direct torque control has some benefits such as faster torque response and reduced torque ripple for driving the brushless DC motors. Because of ignoring stator flux linkage of direct torque control in constant torque region, driving of brushless DC motors is not complicated. In order to solve the problems associated with conventional PI speed controller, a new speed control based on adaptive-neuro fuzzy inference system is proposed to eliminate overshoot in the torque and speed responses, simplify designing and reduce complexity of math formulas. To reduce rising time, PD controller is used with adaptive-neuro-based Fuzzy Inference System. The effectiveness of proposed system has been validated by simulation results.