基于扰动补偿模型预测的自由漂浮空间机器人运动控制
DOI:
CSTR:
作者:
作者单位:

1.哈尔滨工业大学;2.上海宇航系统工程研究所,宇航空间机构全国重点实验室

作者简介:

通讯作者:

中图分类号:

基金项目:

国家自然科学基金项目(面上项目,62373127),中国博士后科学基金(2024M764189),中国航天科技集团公司第八研究院产学研合作基金资助项目(SAST2024-018, SAST2024-019)


Disturbance Compensation Based Model Predictive Motion Control for Free-floating Space Robots
Author:
Affiliation:

Fund Project:

The National Natural Science Foundation of China (General Program, 62373127),China Postdoctoral Science Foundation(2024M764189),Industry-University-Research Cooperation Fund of the Eighth Research Institute of China Aerospace Science and Technology Corporation(SAST2024-018, SAST2024-019)

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    自由漂浮空间机器人凭借其运动自由度高、工作寿命长等优势,已成为长期在轨服务的关键无人设备。然而空间环境变化导致的外部扰动,以及因燃料消耗、系统参数辨识不准确等因素导致的模型不确定性会增加空间机器人高精度控制的难度。本文针对自由漂浮空间机器人存在外部扰动和模型不确定性的场景,设计了一种基于扰动补偿的模型预测控制方法。基于固定时间稳定性理论设计扰动观测器,使扰动估计误差在不依赖于初始误差的常数上界内实现收敛。同时,将扰动估计值补偿入模型预测控制器,提高集总扰动条件下预测模型的准确性,进一步地利用模型预测控制滚动优化的特点,实现了空间机器人约束条件下高精度控制。本文证明了扰动观测器与基于扰动补偿模型预测控制器的稳定性,并通过数值仿真验证了方法的有效性。

    Abstract:

    Free-floating space robots have emerged as critical unmanned platforms for long-term in-orbit services due to their high mobility and extended operational lifespan. However, external disturbances caused by dynamic space environments, as well as model uncertainties arising from fuel consumption and inaccurate system parameter identification, significantly increase the challenges of high-precision control for space robotic systems. This paper proposes a disturbance compensation-based model predictive tracking control method for free-floating space robots subject to joint disturbance torques and model uncertainties. A fixed-time disturbance observer is designed based on fixed-time stability theory, ensuring that the disturbance estimation error converges within a fixed upper bound independent of initial errors. The estimated disturbances are then compensated into the model predictive controller to enhance prediction model accuracy under lumped disturbance conditions. Furthermore, by leveraging the receding horizon optimization characteristics of model predictive control, high-precision trajectory tracking is achieved while satisfying system constraints. The stability of the proposed disturbance observer and the compensation-based model predictive controller is rigorously proven. Numerical simulations are conducted to validate the effectiveness of the proposed approach in improving control precision and disturbance rejection capabilities.

    参考文献
    相似文献
    引证文献
引用本文
分享
相关视频

文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:2025-05-27
  • 最后修改日期:2025-12-14
  • 录用日期:2025-12-15
  • 在线发布日期:
  • 出版日期:
文章二维码
您是第位访问者
网站版权 © 南京航空航天大学学报
技术支持:北京勤云科技发展有限公司