引用本文: | 朱安,陈力.含弹簧阻尼缓冲机构空间机器人捕获卫星操作的 避撞柔顺强化学习控制[J].控制理论与应用,2020,37(8):1727~1736.[点击复制] |
ZHU An,CHEN Li.Collision avoidance and compliance reinforcement learning control for space robot with spring-damper buffer device capturing satellite[J].Control Theory and Technology,2020,37(8):1727~1736.[点击复制] |
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含弹簧阻尼缓冲机构空间机器人捕获卫星操作的 避撞柔顺强化学习控制 |
Collision avoidance and compliance reinforcement learning control for space robot with spring-damper buffer device capturing satellite |
摘要点击 2283 全文点击 953 投稿时间:2019-10-10 修订日期:2020-03-15 |
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DOI编号 10.7641/CTA.2020.90839 |
2020,37(8):1727-1736 |
中文关键词 空间机器人 弹簧阻尼缓冲机构 避撞柔顺策略 冲击效应 强化学习 |
英文关键词 space robot spring-damper buffer device collision avoidance and compliance strategy impact effect reinforcement learning |
基金项目 国家自然科学基金(11372073)和福建省工业机器人基础部件技术重大研发平台(2014H21010011) 资助项目 |
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中文摘要 |
针对空间机器人捕获卫星操作过程中, 关节因受冲击载荷而易造成冲击破坏的问题, 在关节电机与机械臂
之间设计了一种弹簧阻尼缓冲机构. 缓冲机构不仅能利用弹簧实现捕获操作过程的柔顺化, 利用阻尼器实现碰撞
能量的吸收及柔性振动的抑制; 还能通过合理设计与之配合的避撞柔顺策略使关节所受冲击力矩限定在安全范围
内. 首先, 分别利用含耗散力Lagrange方程法与Newton-Euler法导出了碰撞前的空间机器人与被捕获卫星的分体系
统动力学方程; 然后, 结合Newton第三定律、捕获点的速度约束、各分体的位置约束获得了捕获后的混合体系统动
力学方程, 且基于动量守恒关系计算了碰撞冲击效应与冲击力; 最后, 提出了一种结合缓冲机构的避撞柔顺强化学
习控制方案, 该方案通过实时与动态环境试错交互得到惩罚信号, 并利用惩罚信号对控制器进行优化, 实现对失稳
混合体系统的镇定控制. 利用Lyapunov定理证明了系统的稳定性; 数值仿真验证了缓冲结构的抗冲击性能及所提策
略的有效性. |
英文摘要 |
In order to protect joints from impact damage during the process of space robot capturing satellite, a springdamper
buffer device is designed between joint motor and manipulator. The device can not only use spring to achieve the
compliance during the capture operation, use damper to absorb impact energy and suppress flexible vibration; but also limit
the joint’s impact torque to a safe range through reasonable and coordinated design the collision avoidance and compliance
strategy. First of all, the dynamic models of space robot and satellite at collision time are derived by using Lagrange
function based on dissipation theory and Newton-Euler function respectively. After that, combined with Newton’s third
law, velocity and position constraints of capture points constraints of bodies, the dynamic model of hybrid system after
capture is obtained, the impact effect and impact force are calculated based on momentum conservation. Finally, a collision
avoidance and compliance reinforcement learning control strategy with buffer device is proposed. The penalty signal
is obtained by trial-and-error interaction with dynamic environment, be used to optimize the controller to stabilize the
instability hybrid system. The stability of the system is proved by Lyapunov theorem, and the impact resistance of the
device and the effectiveness of the proposed strategy are verified by numerical simulation. |
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