针对压电伺服刀架系统存在着固有的灵敏度低和加工过程中的一系列振动等问题,采用神经网络优化算法,提出了一种新型压电伺服刀架位移输出控制技术。本文首先获得系统传递函数,继而探究其内部联系,最终输出PID闭环阶跃响应曲线。借助于PID控制器,采用BP神经网络算法实现对于该系统的闭环控制。实验结果表明:传统PID控制系统对刀架平台进行控制后,刀架平台输出位移误差降低,平均误差为0.1743 μm,达到稳态值时的响应时间为0.36s。而BP神经网络PID控制技术可以将平均误差缩小至0.1126 μm,响应时间大幅度减少为0.15s,相对于传统控制技术的响应速度、超调量等性能进行了显著改善,同时,综合考虑了具体控制过程中的可靠性。
Abstract
Aiming at a piezoelectric servo tool holder system’s inherent low sensitivity and a series of vibration problems in process,a new piezoelectric servo tool holder displacement output control technique was proposed by using the neural network optimization algorithm. Here,the system transfer function was firstly obtained,then internal relations were explored,and finally the PID closed loop step response curve was outputted. By means of a PID controller,the closed-loop control of the system was realized using the BP neural network algorithm. Test results showed that after the tool holder platform is controlled with a traditional PID controller,its output displacement error is reduced,the average error is 0.174 3 μm,and the response time to reach the steady state value is 0.36 s; using the BP neural network combined with PID control technique,the average error can be reduced to 0.112 6 μm,the response time decreases greatly to reach 0.15 s, compared with the traditional control technique,the control performances,such as,response speed and overshoot are significantly improved,at the same time,the reliability of this control process is comprehensively considered.
关键词
快速伺服刀架系统 /
BP神经网络 /
PID控制器 /
精密定位 /
振动控制
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Key words
Piezoelectric servo turret system /
BP neural network /
PID controller /
precision positioning /
vibration control
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