基于凸优化的严格回归轨道自主轨迹捕获控制

  • 岳杨 ,
  • 王嘉轶 ,
  • 杨盛庆 ,
  • 杜耀珂 ,
  • 王文妍
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  • 上海航天控制技术研究所

收稿日期: 2025-10-22

  修回日期: 2025-12-24

  网络出版日期: 2025-12-25

Convex Optimization Based Autonomous Trajectory Capture for Strictly-regressive Orbit

  • YUE Yang ,
  • WANG Jia-Yi ,
  • YANG Sheng-Qing ,
  • DU Yao-Ke ,
  • WANG Wen-Yan
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Received date: 2025-10-22

  Revised date: 2025-12-24

  Online published: 2025-12-25

摘要

面向卫星严格回归轨道初始化的在轨自主性及鲁棒性运行需求,采用小推力自主制导与控制方法,旨在实现卫星在给定任务时间及管径约束条件下,燃料最优的空间大范围自主轨迹精确捕获。以非奇异相对轨道要素为状态变量,通过管径偏差与相对轨道要素相互映射关系,建立严格回归轨道动力学优化模型,其状态转移矩阵纳入大气阻力摄动、日月三体引力多种摄动效应。通过几何管径约束的二阶锥形式表达,构建起凸优化问题,实现在轨优化实时运行及稳定收敛。对凸优化推力指令正则处理,生成符合推力器实际开关特性的推力序列。通过嵌入模型预测控制的滚动时域架构,将闭环控制转化为时序迭代凸优化问题,确保空间轨迹捕获精度。

本文引用格式

岳杨 , 王嘉轶 , 杨盛庆 , 杜耀珂 , 王文妍 . 基于凸优化的严格回归轨道自主轨迹捕获控制[J]. 航空学报, 0 : 1 -0 . DOI: 10.7527/S1000-6893.2025.32954

Abstract

To meet the on-orbit autonomous and robust operation requirements for satellite strictly-regressive orbit initialization, a low-thrust autonomous guidance and control method is adopted. This method aims to achieve fuel-optimal, large-scale autonomous trajectory capture with high precision under given mission time and tube constraints. Using non-singular relative orbital elements as state variables, an optimized dynamics model for the strictly-regressive orbit is established by mapping the relationship between tube deviations and relative orbital elements. The state transition matrix incorporates various perturbation effects, including atmospheric drag and third-body gravitational perturbations from the Sun and Moon. By expressing the geometric tube constraints in the form of second-order cones, a convex optimization framework is constructed, enabling real-time on-orbit optimization with stable convergence. The thrust commands from the convex optimization are regularized to generate thrust sequences that conform to the practical on-off characteristics of thrusters. Through a receding horizon architecture embedded with model predictive control, the closed-loop control is transformed into a sequential iterative convex optimization problem, ensuring high precision in spatial trajectory capture.

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