基于模糊神经网络滑模控制的xy平台轮廓控制  

Contour Control of xy Table Based on Fuzzy Neural Network Sliding Mode Control

作　　者：王丽梅[1] 左莹莹[1] 

机构地区：[1]沈阳工业大学电气工程学院,辽宁沈阳110870

出　　处：《机床与液压》2014年第11期23-26,共4页Machine Tool & Hydraulics

基　　金：国家自然科学基金资助项目(51175349);辽宁省高等学校优秀人才支持计划资助项目(LR2013006);沈阳市科技计划项目(F13-316-1-48)

摘　　要：永磁同步直线电机(PMLSM)直接驱动xy平台数控系统曲线轨迹跟踪时,其轮廓精度会受负载扰动以及曲线轨迹轮廓误差模型复杂等问题的影响。针对此问题,采用具有自学习能力的模糊神经网络滑模控制(FNNSMC)进行单轴位置控制器的设计,在不失滑模控制鲁棒性的情况下,有效地削弱该控制所产生的抖振;两轴之间运用实时轮廓误差计算法建立曲线轨迹的轮廓误差模型并采用交叉耦合控制(CCC)进行轮廓控制器的设计,实现跟踪误差与轮廓误差的同时减小。仿真结果表明:该控制方案基本消除了抖振,保证xy平台具有较强的鲁棒性和较高的轮廓精度。Complicated contour error model of curve trajectory and load disturbance would influence the contour accuracy of di-rect drive xy table driven by permanent magnet linear synchronous motor.The fuzzy neural network sliding mode control with self-learn-ing ability was adopted for single axis to design position controller.The system not only had strong robustness but also weakened the effects of chattering.Between the two axes,the real time contour error calculation algorithm was adopted to built contour error model of xy table.Then cross-coupled control was adopted to design contour controller.The tracking error and contour error were weakened sim-ultaneously.Simulation results show that the effects of chattering almost do not exist and the control system has strong robustness and high contour precision.

关 键 词：永磁同步直线电机 XY平台 负载扰动 模糊神经网络滑模控制 交叉耦合控制 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]