系统级综合用于持续推进不确定性下快速机会约束故障后上升重规划

中文摘要 AI 辅助

非致命推进故障可能使标称上升轨迹失效，同时仍保留足够的飞行器能力以到达原始轨道或降级目标。确定性重规划可以恢复标称可行性，但识别出的推进能力中的残余不确定性仍可能导致路径约束违反和终端入轨散布。本文开发了一种快速机会约束随机上升轨迹重规划器，明确考虑持续推进不确定性。不确定性模型结合了跨预测范围共享的持续随机不确定性与区间独立扰动。对于固定标称轨迹，使用系统级综合来参数化闭环响应。对系统响应进行基于Cholesky的变换，将由此产生的跨时间相关反馈设计问题转化为共享公共Riccati递推的逐列仿射递推。进一步从无相位修正修正春分点元素中的最小能量入轨后轨道修正推导出任务导向终端权重，从而将终端协方差整形直接与修正需求联系起来。随机重规划问题通过交替进行确定性轨迹重规划和反馈控制器设计来解决，基于协方差的机会约束回退耦合两个更新。非线性蒙特卡洛仿真表明，在多种不确定性水平和故障条件下，等效修正需求降低、机会约束满足有效且在线重规划快速。

英文摘要

A nonfatal propulsion fault can invalidate the nominal ascent trajectory while leaving sufficient vehicle capability to reach the original orbit or a degraded target. Deterministic replanning can restore nominal feasibility, but residual uncertainty in the identified propulsion capability may still lead to path-constraint violations and terminal injection dispersion. This paper develops a fast chance-constrained stochastic ascent trajectory replanner that explicitly accounts for persistent propulsion uncertainty. The uncertainty model combines persistent random uncertainties shared across the prediction horizon with interval-wise independent disturbances. For a fixed nominal trajectory, system level synthesis is used to parameterize the closed-loop responses. A Cholesky-based transformation of the system responses converts the resulting cross-time correlated feedback design problem into column-wise affine recursions that share a common Riccati recursion. A task-oriented terminal weight is further derived from the minimum-energy post-injection orbital correction in phase-free modified equinoctial elements, thereby relating terminal covariance shaping directly to correction demand. The stochastic replanning problem is solved by alternating deterministic trajectory replanning and feedback controller design, with covariance-based chance-constraint backoffs coupling the two updates. Nonlinear Monte Carlo simulations demonstrate reduced equivalent correction demand, effective chance-constraint satisfaction, and fast online replanning over a range of uncertainty levels and fault conditions.

发表机构

• School of Astronautics, Beihang University（北京航空航天大学宇航学院）
• State Key Laboratory of High-Efficiency Reusable Aerospace Transportation Technology（高效可重复使用航天运输技术国家重点实验室）
• National University of Defense Technology（国防科技大学）
• Changsha Aerospace Technology Innovation Institute（长沙航天技术创新研究院）

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