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空间机器人双臂捕获卫星操作的事件采样输出反馈神经网络避撞柔顺控制 被引量:3

Collision avoidance and compliance control based on event sampling output feedback neural network for space robot dual arm capture satellite operation
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摘要 讨论漂浮基空间机器人双臂捕获非合作卫星过程避免关节冲击破坏的避撞柔顺控制问题,提出在机械臂与关节电机之间加入一种旋转型串联弹性执行器(rotatory series elastic actuator, RSEA)作为柔顺缓冲机构,其作用在于:1)捕获碰撞过程,通过其内置弹簧的拉伸或压缩吸收捕获操作过程中被捕获卫星对空间机器人关节产生的冲击能量;2)捕获完成后的镇定过程,利用设计与之配合的避撞柔顺控制策略保证关节冲击力矩限制在安全范围.利用第二类拉格朗日方程推导得到捕获操作前含柔顺机构双臂空间机器人系统及目标卫星的各分体系统动力学模型;基于系统动量守恒关系、系统运动几何关系及牛顿第三定律,得到捕获操作后双臂空间机器人与被捕获卫星混合体系统综合动力学方程;针对捕获操作后受碰撞影响而产生不稳定运动的混合体系统,提出一种基于事件采样输出反馈的RBF神经网络避撞柔顺控制方案.上述方案与柔顺机构相结合不仅能有效吸收被捕获卫星的冲击能量,还能在冲击能量过大时应时开、关双臂空间机器人关节电机,以防止关节电机发生过载和破坏.通过李雅普诺夫稳定性理论证明系统的全局稳定性,并通过仿真结果验证所提避撞柔顺控制方案的有效性. This paper studies the collision avoidance and compliant control for free-floating space robot double arm capture satellites, and a rotating series elastic actuator(RSEA) is proposed and adopted between the manipulator and the joint motor as a compliant mechanism. Its functions are as follows: 1) the impact energy of the captured satellite on the joint of a space robot can be absorbed by the deformation of the internal spring;2) the joint impact torque can be limited to a safe range through combining with the collision avoidance compliant control scheme. The dynamic models of the space robot and the target satellite before capture are derived by using the second Lagrange equation. Then, based on the momentum conservation relationship, the kinematic geometry relationship and Newton’s third law, the integrated dynamic model of the combined system is obtained. Finally, considering the post-capture unstable combined system, a kind of RBF neural network collision avoidance compliance control scheme based on the event sampling output feedback is proposed, which can not only effectively absorb the impact energy of the captured satellite, but also turn on and off the joint motor when the impact energy is too large. The global stability of the system is proved by Lyapunov stability theory,and the effectiveness of the proposed collision avoidance compliance control scheme is verified by simulation.
作者 曾晨东 艾海平 陈力 ZENG Chen-dong;AI Hai-ping;CHEN Li(School of Mechanical Engineering and Automation,Fuzhou University,Fuzhou 350116,China)
出处 《控制与决策》 EI CSCD 北大核心 2021年第9期2113-2122,共10页 Control and Decision
基金 国家自然科学基金项目(11372073) 福建省工业机器人基础部件技术重大研发平台项目(2014H21010011)。
关键词 空间机器人 双臂捕获卫星操作 事件采样 RBF神经网络 避撞柔顺控制 space robot double arm capture satellite operation event sampling RBF neural network collision avoidance and compliance control
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