Adaptive Control for Brushless DC Motor Based on Fuzzy Inference

Due to the nonlinearity of brushless direct current (BLDC) motor, it is difficult to obtain satisfied control characteristics using proportional integral derivative (PID) controller. A novel adaptive fuzzy control method based on high performance speed control is proposed in this paper, which combines an adaptive parameter adjustment mechanism with fuzzy controller to solve the problems of non-linearity, parameter variations and load excursions that occur in the BLDC motor drive system. The adaptive parameter adjustment mechanism can give better quantization and proportion factors of the fuzzy controller when there are variations in motor parameters or load, hence the fuzzy control rules are changed. The adaptive fuzzy control system is simulated in matlab with the changes of motor parameters and load, the control performance of the traditional PID controller is compared with the adaptive fuzzy controller. The comparison results indicate that the adaptive fuzzy control system has stronger robust and self-adaptive ability, faster response time, and zero overshoot and steady state error, which can satisfy the request of the BLDC motor control system. DOI : http://dx.doi.org/10.11591/telkomnika.v12i5.4950

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