Abstract The free-flying space manipulators present challenges in controlling the motions of both the spacecraft bus and the manipulator, because of the highly-coupling system dynamics and the unknown space environment disturbances. Although the sliding mode controllers are robust to the unknown disturbances and system uncertainties, the chattering effect could affect the pointing accuracy and the lifetime of the actuators. This paper first introduces the dynamics of a CuBot, which is a 3-rigid-link manipulator based on the CubeSat platform. To maintain the robustness while decreasing the chattering effect, an innovative reinforcement learning based fuzzy adaptive sliding mode controller is proposed. To maintain the robustness while reducing the chattering effect, an innovative reinforcement learning based fuzzy adaptive sliding mode controller is proposed. The switching gain is updated to estimate the lumped upper bound of the system uncertainties and the unknown disturbances, and then a new fuzzy logic adaptive law is applied on the switching gain to decrease the chattering effects. On top of that, the fuzzy logic rules are tuned by an innovative modified reinforcement learning mechanism to achieve the better tracking performance. The uniformly ultimately bounded tracking errors are guaranteed by the proposed control scheme, and the effectiveness is validated by the simulation results.

中文翻译：

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基于强化学习的模糊滑模控制的空间机械手运动控制

摘要 由于高度耦合的系统动力学和未知的空间环境扰动，自由飞行的空间机械臂在控制航天器总线和机械臂的运动方面提出了挑战。尽管滑模控制器对未知干扰和系统不确定性具有鲁棒性，但颤振效应会影响指向精度和执行器的使用寿命。本文首先介绍了 CuBot 的动力学，它是一个基于 CubeSat 平台的 3 刚性连杆机械手。为了在保持鲁棒性的同时减少颤动效应，提出了一种基于强化学习的新型模糊自适应滑模控制器。为了保持鲁棒性，同时减少颤振效应，提出了一种创新的基于强化学习的模糊自适应滑模控制器。更新开关增益以估计系统不确定性和未知扰动的集总上限，然后对开关增益应用新的模糊逻辑自适应律以减少颤振效应。最重要的是，模糊逻辑规则通过创新的改进强化学习机制进行调整，以实现更好的跟踪性能。所提出的控制方案保证了一致最终有界的跟踪误差，仿真结果验证了其有效性。然后对开关增益应用新的模糊逻辑自适应律以减少颤振效应。最重要的是，模糊逻辑规则通过创新的改进强化学习机制进行调整，以实现更好的跟踪性能。所提出的控制方案保证了一致最终有界的跟踪误差，仿真结果验证了其有效性。然后对开关增益应用新的模糊逻辑自适应律以减少颤振效应。最重要的是，模糊逻辑规则通过创新的改进强化学习机制进行调整，以实现更好的跟踪性能。所提出的控制方案保证了一致最终有界的跟踪误差，仿真结果验证了其有效性。