直驱XY平台伺服系统的递归神经网络鲁棒跟踪控制

Recursive Neural Network Robust Tracking Control of Linear Drive XY Table Servo System

针对永磁直线同步电机驱动的XY平台存在的系统滞后、未建模动态、系统参数变化摩擦力以及外部负载扰动等不确定性因素对伺服系统性能的影响,提出一种递归神经网络控制方法,来控制XY平台伺服系统的运行状态,以达到鲁棒精密跟踪控制的目的。由于递归神经网络是一种动态的映射结构,对上述不确定性均能有效控制,它具有前馈和反馈两种的网络连接方式,同时递归神经元具有内部的反馈回路,不需外部的延时反馈,即可获得系统的动态响应。仿真实验结果表明,所设计的控制系统具有较强的鲁棒性能和快速跟踪性能,大大减小了系统的轮廓误差,提高了系统的定位精度。

Aimed at the existed uncertain factors affecting the performance of the servo system in the XY table driving by perma-nent magnet linear synchronous motor,such as the system lag,non-modeled dynamics,system parameters variation,friction,external load disturbance and so on,a kind of recursive neural network control method is proposed to control the operation state of the servo sys-tem,so as to achieve the robust precision tracking control purposes.Since the recursive neural network was a dynamic mapping struc-ture,the uncertainty mentioned above could all be controlled effectively,which had two kinds of feedforward and feedback connection methods for network.At the same time recursive neuron had an internal feedback loop,the dynamic response of the system could be obtained without external delay feedback.The experimental simulation results show that,the designed control system has quite strong robustness and fast tracking performance,which can greatly reduce the contour error of the system,and improve the positioning accura-cy of the system.