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采用双电机驱动的数控机床,常出现同步误差,使工作台受到不平衡扭矩的作用,影响了机床的加工精度。将模糊推理与神经网络相结合,提出模糊神经PID控制策略,实现PID控制参数的实时调整;同时,把伺服电机的控制电流和丝杠的实时位置作为衡量指标,进行仿真分析和实验研究。结果表明:该方法能有效减小同步误差,提高工件加工精度,较好地满足被控对象对高精度的要求,具有一定的实际应用价值。
The use of dual-motor-driven CNC machine tools, often appear synchronization error, the workbench imbalance torque, affecting the machining accuracy. Combining fuzzy reasoning and neural network, a fuzzy neural PID control strategy is proposed to realize the real-time adjustment of PID control parameters. At the same time, the control current of the servo motor and the real-time position of the lead screw are taken as the indexes to carry on the simulation analysis and experimental research. The results show that this method can effectively reduce the synchronization error, improve the machining accuracy and meet the requirements of the accused object with high precision, which has a certain practical value.