Abstract：According to the difficulty of control parameters tuning for electromechanical actuator(EMA) servo system, a new method of off-line tuning proportional integral(PI) controller’s coefficients is proposed, which based on error back propagation(BP) Artificial neural network(ANN) and genetic algorithm(GA). BP Artificial neural network(BP-ANN) is trained using EMA servo system experimental data, and the highest prediction precision BP-ANN model’s outputs are chosen as optimal objective function of the genetic algorithm’s inputs, then optimal values of PI controller’s coefficients were obtained through using genetic algorithm to quick research, which ensuring the perfect dynamic response performance of the whole system. The MEA system driving by brushless DC motor(BLDC) was used to carry out speed control experiment. The results adopting the optimal PI controller’s coefficients show that the system’s output can follow the input instruction change rapidly, steadily and accurately, and it has strong anti-interference ability as well.
崔业兵, 郑健, 鞠玉涛, 赵金星. 舵机永磁无刷直流电机控制器参数离线整定[J]. 电工技术学报, 2013, 28(9): 281-287.
Cui Yebing, Zheng Jian, Ju Yutao, Zhao Jinxing. Off-Line Controller Parameters Tuning for Electromechanical Actuator Systems with Permanent Magnet Brushless DC Motor Driving. Transactions of China Electrotechnical Society, 2013, 28(9): 281-287.
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2013, Vol. 28 
