基于模糊CMAC神经网络的XY平台交叉耦合控制

针对永磁直线同步电机(PMLSM)驱动的XY平台系统的负载扰动、任意加工曲线轮廓误差模型复杂及双轴参数不匹配等会影响加工精度的问题,XY平台单轴采用了能反映人脑认知模糊性和连续性的模糊小脑模型关节控制器(FCMAC)设计速度控制器,在两轴之间采用实时轮廓误差估计模型和交叉耦合控制(CCC)进行轮廓控制器的设计,可同时减小跟踪误差和轮廓误差.FCMAC可准确及时地抑制负载扰动,交叉耦合控制削弱了双轴参数不匹配的影响.仿真结果表明,所设计的XY平台控制系统具有较高的轮廓精度和较强的鲁棒性.

Cross-coupled control for XY table based on fuzzy-CMAC neural network

In order to solve the problem that the processing accuracy of XY table driven by permanent magnet linear synchronous motor （PMLSM） is influenced by the load disturbance, complicated contour error model of any processing trajectory and biaxial parameter mismatch, a fuzzy cerebella model articulation controller （FCMAC） reflecting the fuzziness and continuity of human cerebella cognition was used to design the speed controller for single axis of XY table. The real time contour error estimation model and cross coupled control （CCC） were adopted to design the contour controller between the two axes. And thus, the tracking error and contour error are simultaneously reduced. The FCMAC can suppress the load disturbance accurately and timely, and the cross coupled control weakens the influence of biaxial parameter mismatch. The simulated results show that the designed control system of XY table possesses stronger robustness and higher contour precision.