带执行器饱和的N 连杆机械臂输出反馈动态面控制

针对带执行器饱和的多关节刚性机械臂系统,提出一种基于RBF神经网络补偿的输出反馈动态面控制.通过观测器实现角速度的观测,采用RBF网络实现执行器饱和的补偿;通过Lyapunov方法证明闭环系统的稳定性,实现高精度的角度和角速度跟踪.仿真结果表明,所提出的方法能够有效补偿系统存在的执行器饱和,显著减小跟踪误差,并且对于外界干扰具有一定的鲁棒性.

Output feedback dynamic surface control for N link manipulators with ctuator saturation ctuator saturation

The RBF neural network compensation based output feedback dynamic surface controller is proposed for N link manipulators with actuator saturation. An observer is designed to estimate unknown velocity states. The RBF neural network is designed to overcome the saturation nonlinearity. Based on the Lyapunov stability analysis, it is proved that the control strategy can guarantee the stability of the closed-loop system, and high tracking performance can be achieved by adjusting the controller parameters. Simulation results show that the proposed control system can compensate for the actuator saturation effectively, reduce the tracking error dramatically and improve tracking performance, and the control system shows robustness to external disturbances.