空间机器人双臂捕获航天器后姿态管理、辅助对接操作一体化ELM神经网络控制

发布时间：2018-11-11 22:05

【摘要】：讨论了空间机器人双臂捕获航天器后姿态管理和辅助对接操作的协调控制问题.首先,利用冲量定理、闭环约束几何及运动学条件获得了捕获操作后闭链混合体系统的动力学方程,并分析了混合体系统受到的冲击效应.其次,针对捕获操作后系统姿态受扰运动镇定及辅助对接操作需求,对闭链混合体系统提出了基于极限学习机(ELM)的自适应神经网络控制方案,极限学习机具有学习速度快、仅需调节网络输出权值等优点,可用于逼近系统的未知动力学模型.该方案不要求系统动力学方程关于惯性参数呈线性函数关系,并且不需要精确的系统动力学模型.通过李亚普诺夫方法设计了ELM网络的权值自适应律及鲁棒项,以保证系统的载体姿态受扰运动镇定与对接操作过程的位置及角度的精确控制,并证明了系统的稳定性.为保证各臂协同操作,运用加权最小范数法分配力矩.最后,通过系统数值仿真模拟了碰撞冲击效应及闭链系统的运动过程.所提控制方案可以有效完成载荷、载体运动控制及辅助对接操作.
[Abstract]:In this paper, the problem of attitude management and coordinated control of docking operation for space robot after two arm capture spacecraft is discussed. Firstly, by using impulse theorem, closed loop constrained geometry and kinematics conditions, the dynamic equations of closed chain hybrid system after capture operation are obtained, and the shock effect of the hybrid system is analyzed. Secondly, aiming at the requirement of attitude disturbance stabilization and auxiliary docking operation, an adaptive neural network control scheme based on extreme learning machine (ELM) is proposed for closed chain hybrid system. The ultimate learning machine has fast learning speed. It can be used to approximate the unknown dynamic model of the system only by adjusting the output weights of the network. This scheme does not require the system dynamics equation to be linear function relation about the inertial parameter, and does not need the accurate system dynamics model. The weight adaptive law and robust term of ELM network are designed by Lyapunov method to ensure the precise control of the position and angle of the attitude disturbance motion stabilization and docking operation of the system, and the stability of the system is proved. In order to ensure the cooperative operation of each arm, the weighted minimum norm method is used to distribute the torque. Finally, the impact effect and the motion process of the closed chain system are simulated by numerical simulation. The proposed control scheme can effectively complete load, carrier motion control and auxiliary docking operation.
【作者单位】：福州大学机械工程及自动化学院福建省高端装备制造协同创新中心;
【基金】：国家自然科学基金(11372073,11072061)
【分类号】：TP242;V441

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