摘要
对存在模型误差和外部扰动信号的刚性机器人,提出采用计算力矩和模糊神经网络补偿相结合的控制方法,实现了刚性机器人轨迹跟踪鲁棒控制。该控制方案不仅可以简单得到精确在线训练数据,而且克服了神经网络控制实时性差的弱点。仿真结果表明,采用模糊神经网络作为补偿控制器,既能消除不确定性对系统的影响,又能得到渐近收敛的跟踪误差。
The method of robust tracking control using a computed torque method and a fuzzy neural network （FNN） compensator for a rigid robotic manipulator with uncertain dynamics and external disturb signals was presented. And a novel method to obtain true teaching signals for the FNN and overcome the real-time control problems existed in the neural network control was presented. The simulation results show that the effects of large system uncertainties can be eliminated and asymptotic convergence of the output tracking error can be guaranteed by using a FNN compensator in the closed loop feedback control system for the rigid robotic manipulator.
出处
《机床与液压》
北大核心
2007年第7期135-137,140,共4页
Machine Tool & Hydraulics
