使用深度强化学习的航天器反作用轮姿态智能控制
Intelligent Control of Spacecraft Reaction Wheel Attitude Using Deep Reinforcement Learning
AI总结：
本研究提出TD3-HD深度强化学习控制策略，通过结合TD3、HER和DWC提升卫星反作用轮故障下的容错性与适应性，实验证明其姿态误差更低、稳定性更强。
摘要：
可靠的卫星姿态控制对于空间任务的成功至关重要，特别是随着卫星越来越多地在动态和不确定的环境中自主运行。反作用轮（RWs）在姿态控制中起着关键作用，在RW故障期间保持控制弹性对于维护任务目标和系统稳定性至关重要。然而，传统的比例微分（PD）控制器和现有的深度强化学习（DRL）算法（如TD3、PPO和A2C）通常无法提供自主卫星操作所需的实时适应性和容错性。本研究引入了一种基于DRL的控制策略，旨在提高卫星在故障条件下的弹性和适应性。具体而言，所提出的方法将双延迟深度确定性策略梯度（TD3）与事后经验回放（HER）和维度裁剪（DWC）相结合，称为TD3-HD，以增强在稀疏奖励环境中的学习，并在RW故障期间保持卫星稳定性。所提出的方法与PD控制和领先的DRL算法进行了基准比较。实验结果表明，TD3-HD在故障条件下实现了显著更低的姿态误差、改进的角速度调节和增强的稳定性。这些发现强调了所提出方法作为自主卫星姿态控制的强大、容错、机载AI解决方案的潜力。
英文摘要：
Reliable satellite attitude control is essential for the success of space missions, particularly as satellites increasingly operate autonomously in dynamic and uncertain environments. Reaction wheels (RWs) play a pivotal role in attitude control, and maintaining control resilience during RW faults is critical to preserving mission objectives and system stability. However, traditional Proportional Derivative (PD) controllers and existing deep reinforcement learning (DRL) algorithms such as TD3, PPO, and A2C often fall short in providing the real time adaptability and fault tolerance required for autonomous satellite operations. This study introduces a DRL-based control strategy designed to improve satellite resilience and adaptability under fault conditions. Specifically, the proposed method integrates Twin Delayed Deep Deterministic Policy Gradient (TD3) with Hindsight Experience Replay (HER) and Dimension Wise Clipping (DWC) referred to as TD3-HD to enhance learning in sparse reward environments and maintain satellite stability during RW failures. The proposed approach is benchmarked against PD control and leading DRL algorithms. Experimental results show that TD3-HD achieves significantly lower attitude error, improved angular velocity regulation, and enhanced stability under fault conditions. These findings underscore the proposed method potential as a powerful, fault tolerant, onboard AI solution for autonomous satellite attitude control.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
