Application of modern deep learning to satellite attitude control

现代深度学习在卫星姿态控制中的应用

• 批准号: 2605755
• 金额: --
• 依托单位: University of Glasgow
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2605755
• 关键词: Application; modern; deep; learning; satellite

Satellite autonomy and machine learning are areas of growing research interest. Satellite attitude controllers are often developed for certain satellites which have specific mass distributions, which make use of a specific actuator, and attempt to achieve a specific attitude alignment objective. While there are general controllers which can be used for various satellites, such as PID controllers, these often do not achieve optimal performance. A new direction is to consider deep reinforcement learning for satellite attitude control.

卫星自主和机器学习是人们越来越感兴趣的研究领域。卫星姿态控制器通常是针对具有特定质量分布的卫星，利用特定的执行器，试图实现特定的姿态对准目标而开发的。虽然有通用控制器可用于各种卫星，如PID控制器，这些往往不能达到最佳性能。在卫星姿态控制中考虑深度强化学习是一个新的发展方向。