BLDC Motor Control System Based on Quadratic Single Neuron Adaptive PID Algorithm

Xiaoyuan Wang, Tao Fu and Xiaoguang Wang
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Xiaoyuan Wang: School of Electrical Engineering and Automation, Tianjin University, Tianjin, China
Tao Fu: School of Electrical Engineering and Automation, Tianjin University, Tianjin, China
Xiaoguang Wang: School of Electrical Engineering and Automation, Tianjin University, Tianjin, China

International Journal of Advanced Pervasive and Ubiquitous Computing (IJAPUC), 2014, vol. 6, issue 1, 12-25

Abstract: Brushless DC (BLDC) motors are widely used for many industrial applications because of their high efficiency, high torque and low volume. In view of the problem that the current control method of speed regulation system of BLDC motor has poor control effect caused by fixed parameters of PID controller, an adaptive PID algorithm with quadratic single neuron (QSN) was designed. Quadratic performance index was introduced in adjustment of weight coefficients; expected optimization effect was gotten by calculating control law. QSN adaptive PID controller can change its parameters online when operating conditions are changed, it can also change its control characteristic automatically. Matlab simulations and experiment results showed that the proposed approach has less overshoot, faster response, stronger ability of anti-disturbance, the results also showed more effectiveness and efficiency than the conventional PID model in motor speed control.

Date: 2014
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