神经滑模控制在机器人轨迹跟踪中的应用

针对滑模控制在机器人轨迹跟踪中应用时出现的抖振问题,提出了基于滤波器的神经滑模趋近律控制方法.根据滑模变结构和径向基函数(RBF)神经网络控制理论,并结合滤波器,对两关节机器人的轨迹跟踪控制进行了仿真研究.通过对单纯的滑模变结构加滤波器的控制方法、RBF神经滑模等效控制和RBF神经滑模趋近律控制这三种方法进行对比仿真分析,结果表明设计的神经网络滑模趋近律控制系统具有良好的跟踪性、鲁棒性和较高的控制精确度,同时有效地消除了抖振,实现简单.

Application of neural networks sliding-mode control in tracking control of robot manipulators

Sliding-mode control for trajectory tracking in robot application constantly occurs buffeting,with the problem proposing the neural sliding mode control method based on the filter. According to sliding mode variable structure control theory and neural networks,combining the filter,the two joint robot trajectory tracking control had been simulated and studied. Through the filter and simple sliding mode control method,Radial Basis Function neural worker sliding mode equivalent controlled and the method of RBF neural sliding mode reaching law,the three kinds of method had been compared with and simulatedly analysed. The results show that the design of neural network sliding mode reaching law control system has good tracking,robustness and a high control precision,simple achievement,and effectively eliminated buffeting.