中国科技核心期刊

中文核心期刊

CSCD来源期刊

空间控制技术与应用 ›› 2023, Vol. 49 ›› Issue (3): 54-63.doi: 10.3969/j.issn.1674 1579.2023.03.007

• 论文与报告 • 上一篇    下一篇

失效航天器等离子羽流消旋建模与最优制导研究

  

  1. 西北工业大学航天学院
  • 出版日期:2023-06-26 发布日期:2023-07-14
  • 基金资助:
    国家自然科学基金资助项目(12072270)和国家重点研发计划资助项目(2021YFA0717100)

Modeling and Optimal Guidance of Plasma Plume Detumbling for Failed Spacecraft

  • Online:2023-06-26 Published:2023-07-14

摘要: 为克服等离子羽流无序性强、动力学模型复杂的问题,使用神经网络建立消旋力矩快速计算模型,实现高效、高精度的消旋动力学解算.针对传统制导律难以处理复杂翻滚目标的弊端,提出章动抑制原则,并建立自旋章动耦合目标的最优羽流指向制导律.仿真结果表明基于神经网络的高效计算模型可在同等精度下大幅度减少力矩计算时间,最优制导律可实现复杂章动目标的快速稳定.本研究从在轨计算与任务执行策略两方面显著提升了消旋效率,为利用等离子羽流的在轨操控任务奠定了理论基础.

关键词: 失效航天器, 消旋, 等离子羽流, 神经网络, 最优制导律

Abstract: In order to achieve efficient and high precision torque calculation, a plasma flow detumbling model based on neural network is established. To address the limitations of traditional guidance laws in handling complex tumbling targets, the principle of nutation stabilization is defined, and an optimal guidance law is designed for plasma flow direction. Simulation results indicate that the rapid dynamics model based on neural network can significantly reduce the torque calculation time while maintaining the same precision. The optimal guidance law can rapidly stabilize complex nutation target. This study significantly improves detumbling efficiency from both onorbit calculation and mission strategy, laying the theoretical foundation for onorbit service based on plasma flow.

Key words: failed spacecraft, detumbling, plasma plume, neural network, optimal guidance law

中图分类号: 

  • V448.2