A Fuzzy Logic Reinforcement Learning Control with Spring-Damper Device for Space Robot Capturing Satellite
An Zhu, Haiping Ai, Li Chen
- 发表年份
- 2022
- 引用次数
- 18
- 访问权限
- 开放获取
摘要
In order to prevent joints from being damaged by impact force in a space robot capturing satellite, a spring-damper device (SDD) is added between the joint motor and manipulator. The device can not only absorb and attrition impact energy, but also limit impact force to a safe range through reasonable design compliance control strategy. Firstly, the dynamic mode of the space robot and target satellite systems before capture are established by using a Lagrange function based on dissipation theory and Newton-Euler function, respectively. After that, the impact effect is analyzed and the hybrid system dynamic equation is obtained by combining Newton’s third law, momentum conservation, and a kinematic geometric relationship. To realize the buffer compliance stability control of the hybrid system, a reinforcement learning (RL) control strategy based on a fuzzy wavelet network is proposed. The controller consists of a performance measurement unit (PMU), an associative search network (ASN), and an adaptive critic network (ACN). Finally, the stability of system is proved by Lyapunov theorem, and both the impact resistance of SDD and the effectiveness of buffer compliance control strategy are verified by numerical simulation.
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