基于神经网络的自由漂浮空间机器人关节空间鲁棒跟踪控制

NEURAL NETWORK BASED ROBUST TRAJECTORY TRACKING CONTROL IN JOINT SPACE FOR FREE-FLOATING SPACE ROBOT

针对存在不确定性以及干扰的自由漂浮空间机器人关节空间轨迹跟踪问题,提出了一种基于鲁棒控制思想的神经网络鲁棒控制方法.对于控制器中由系统惯性参数不确定性引起的非线性不确定项,利用径向基函数(RBF)神经网络进行逼近,并且利用鲁棒控制器使系统镇定并保证从干扰到跟踪误差的增益小于或等于给定的指标.最后,对本文提出的控制方案进行数值仿真.仿真结果表明跟踪轨迹误差能以较快的速度收敛到零,从而验证了所提出方法的有效性.

Considering the model uncertainty and disturbances of Free-Floating space Robot,an Neural Network based robust control scheme is proposed aim to solve the problem of trajectory tracking in joint space for free floating space robot.Using RBF neural network to approximate the nonlinear function of controller,robust controller is used to compress the approximation error and external disturbance.The presented control scheme can stabilize the system and guarantee the gain from disturbance to tracking error is lower than the given index.Simulation results show the feasibility of the proposed control scheme.