刚柔空间机器人基于神经网络的协调运动控制及柔性振动抑制

Coordinated Motion Control and Vibration Suppression of Rigid-Flexible Space Robot Based on Neural Network

探讨了本体姿态受控的刚柔耦合空间机器人关节运动控制及柔性振动抑制问题.基于拉格朗日方法及奇异摄动理论,导出了系统的奇异摄动模型.为确保系统在未知惯性参数影响下本体姿态、关节协调运动的精确跟踪控制,针对慢变子系统,提出了一种基于RBF神经网络的补偿控制策略;同时针对快变子系统,采用惯常的线性二次型最优控制器以实现系统柔性振动的主动抑制.仿真结果表明,所提控制方案可有效补偿未知系统惯性参数的影响,使系统能够准确跟踪所期望的运动轨迹,并较好地抑制系统的柔性振动.

The joint motion control and vibration suppression problems of rigid-flexible space robot with an attitude controlled base were discussed. With Lagrangian method and singular perturbation theory, the singular perturbation model of the system was derived. To guarantee the accurate coordinated motion control of the base attitude and the arm＇s joints under the effects of unknown system parameters, the compensation control strategy based on Radial Basis Function （RBF） neural network was proposed for the slow subsystem. Simultaneously, the linear quadratic optimal controller was given for the fast subsystem to suppress the elastic vibration of the system. Simulation results demonstrate that the presented control scheme can effectively compensate for the influence of unknown system parameters, and control the system to track the desired trajectory and suppress the elastic vibration preferably.