Abstract：The motor servo control of machine tools influences the processing efficiency and processing quality of the machine tool. Most servo motor controllers use the proportional integral derivative (PID) control which depends on accurate determination of the control parameters. However, accurate determination of the control parameters requires much time, effort and experience with manual tuning usually required to provide the desired accuracy. This paper presents a method for tuning servo control parameters based on a genetic algorithm. A theoretical model is developed and refined based on the machine tool conditions. The fitness function is developed based on the parallel and hybrid machine tool characteristics with alarm indexes and optimal indexes. The servo control parameters given by the genetic algorithm are then tested on a 5-axis hybrid machine tool. The results show that the optimized parameters give better servo motor following accuracy than the engineer's parameters.Thus, this parameter tuning method based on a genetic algorithm saves time and effort while giving more accurate servo control parameters.
王立平, 孔祥昱, 于广. 基于遗传算法的并混联机床电机伺服控制参数整定[J]. 清华大学学报（自然科学版）, 2021, 61(10): 1106-1114.
WANG Liping, KONG Xiangyu, YU Guang. Motor servo control parameter tuning for parallel and hybrid machine tools based on a genetic algorithm. Journal of Tsinghua University(Science and Technology), 2021, 61(10): 1106-1114.
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2021, Vol. 61 
