驱动电机伺服控制对机床加工效率、加工质量都有影响。伺服电机控制方法中应用最广泛的是比例积分微分（PID）控制，其控制效果与控制参数直接相关，而以往由工程师凭经验进行参数整定，费时费力。该文提出一种基于遗传算法的伺服控制参数整定方法。建立了理论模型，并综合多种条件进行了修正。针对并混联机床的特点提出包含报警指标、择优指标2类指标的适应度函数，得到遗传算法整定的伺服控制参数，并在五轴混联机床上进行了实验。实验结果显示：优化参数下，伺服电机跟随性能优于人工整定参数，进而验证了所提出的基于遗传算法的参数整定方法可以得到更好的性能且省时省力。
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.
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