基于优化的编队飞行在摄动点轨道上
Optimization-Based Formation Flight on Libration Point Orbits
AI总结：
本文提出了一种基于优化的模型预测控制方法，用于在摄动点轨道上保持航天器编队飞行，通过非凸优化问题求解并解决路径约束问题，实现高效且可行的编队维持。
摘要：
一种模型预测控制（MPC）框架被开发用于航天器沿摄动点轨道进行编队飞行的保持任务。在每个控制周期内，MPC策略解决一个多航天器最优控制问题（MVOCP），以跟踪参考轨迹，同时对编队的相对运动施加路径约束。控制策略利用一组有限的控制节点，这些节点符合操作约束，只允许每个轨道周期内进行少量机动机会。为了促进递归可行性，路径约束在预测时间范围内逐步收紧。使用等周改写约束以防止样本间违反。所得到的MVOCP是一个非凸问题，通过顺序凸编程求解。所提出的方法在高保真轨道模型下进行评估，该模型考虑了现实中的不确定性，针对沿近矩形环形轨道（NRHO）的编队，并施加了航天器间分离和相对太阳方位角的路径约束。结果表明，该方法能够维持满足路径约束的航天器编队，其累积推进剂消耗量与现有方法相当。
英文摘要：
A model predictive control (MPC) framework is developed for station-keeping in spacecraft formation flight along libration point orbits. At each control period, the MPC policy solves a multi-vehicle optimal control problem (MVOCP) that tracks a reference trajectory, while enforcing path constraints on the relative motion of the formation. The control policy makes use of a limited set of control nodes consistent with operational constraints that allow only a small number of maneuver opportunities per revolution. To promote recursive feasibility, path constraints are progressively tightened across the prediction horizon. An isoperimetric reformulation of the constraints is used to prevent inter-sample violations. The resulting MVOCP is a nonconvex program, which is solved via sequential convex programming. The proposed approach is evaluated in a high-fidelity ephemeris model under uncertainties for a formation along the near-rectilinear halo orbit (NRHO), and subject to path constraints on inter-spacecraft separation and relative Sun phase angle. The results demonstrate maintenance of a spacecraft formation that satisfies the path constraints with realistic cumulative propellant consumption.
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