可重复使用运载器末端能量管理段自主轨迹重构与智能制导方法研究

Reusable launch vehicle is an inevitable trend in the development of space transportation system with important research value. The terminal area energy management phase is a critical flight phase during the reentry process, where the vehicle should fly in strict accordance with the reference trajectory. However, with the effects of various deviations, disturbances and unexpected events, the vehicle may deviate from the preset reference trajectory. Therefore, this project aims to solve the problem of autonomous trajectory reconstruction and intelligent guidance in the terminal area energy management phase, to improve the intelligence level of the guidance system and ensure the successful completion of the reentry and landing tasks. The principal innovations of this project are: (1) to propose a consumption pattern of the surplus energy based on snake maneuver principle, which simplifies the design of the three-dimensional reference profile of terminal area energy management phase; (2) to propose an online autonomous reconstruction algorithm of the optimal reference trajectory based on the range prediction algorithm, which can determine the reconstruction strategy according to the current state, and can optimize the three-dimensional profile online; (3) to propose an intelligent guidance algorithm based on the adaptive dynamic programming, which can realize the online intelligent calculation of the guidance command, and can reach the approach and landing interface with high precision by tracking the reconstructed reference trajectory adaptively.

可重复使用运载器是航天运输系统发展的必然趋势，具有重要的研究价值。末端能量管理段是其再入返回过程中的关键阶段，必须严格按照参考轨迹飞行，然而，各种偏差、干扰以及突发异常事件的影响会使飞行器严重偏离预设的参考轨迹。因此，本项目旨在解决末端能量管理段的自主轨迹重构和智能制导问题，以提高制导系统的智能化水平，保证再入返回着陆任务的顺利完成。本项目的主要创新点有：（1）根据蛇形机动原理，提出基于航向调整圆和能量耗散圆的富余能量消耗模式，简化末端能量管理段三维参考剖面的设计形式；（2）提出基于航程预测的最优轨迹在线自主重构算法，根据重构时刻的飞行状态自主确定重构策略，并对三维剖面的设计参数进行动态优化求解；（3）提出基于自适应动态规划的智能制导算法，实现制导指令的在线智能求解，对在线重构的参考轨迹进行自适应稳定跟踪，以高精度到达自动着陆窗口。

可重复使用运载器(RLV)高度融合并发展了航天技术和航空技术，功能、结构和飞行方式都非常复杂，是航天运输系统发展的必然趋势，具有重要的军事价值和民用价值。本项目围绕RLV的未来发展目标，以RLV无动力再入返回过程中的关键阶段末端能量管理段为研究对象，针对滑翔飞行水平着陆方式的飞行要求以及末端能量管理段复杂的飞行环境，对末端能量管理段的飞行轨迹剖面和制导回路进行研究。本项目基于优化理论和自适应动态规划理论，从运动建模与三维参考剖面设计、最优轨迹在线自主重构、智能制导技术以及仿真平台搭建等四个方面进行研究，解决了复杂飞行环境下末端能量管理段的自主轨迹重构和智能制导问题，项目成果可以集成应用于RLV的制导系统中，不仅可以提升RLV制导系统的理论研究水平，而且可以推动人工智能技术与航天工程的深度融合，推动我国RLV飞行技术的发展，提高RLV的自主性、安全性、可靠性，降低未来航天运输的成本。