多滑翔飞行器时间协同轨迹快速规划

刘哲; 陆浩然; 郑伟; 闻国光; 王奕迪; 周祥

doi:10.7527/S1000-6893.2020.24497

航空学报 >

2021 , Vol. 42 >Issue 11: 524497 - 524497

DOI: https://doi.org/10.7527/S1000-6893.2020.24497

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多滑翔飞行器时间协同轨迹快速规划

刘哲 ,
陆浩然 ,
郑伟 ,
闻国光 ,
王奕迪 ,
周祥

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1. 国防科技大学空天科学学院, 长沙 410073;
2. 北京宇航系统工程研究所, 北京 100076;
3. 北京交通大学理学院, 北京 100093

收稿日期: 2020-07-04

修回日期: 2020-07-26

网络出版日期: 2020-09-14

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Rapid time-coordination trajectory planning method for multi-glide vehicles

LIU Zhe ,
LU Haoran ,
ZHENG Wei ,
WEN Guoguang ,
WANG Yidi ,
ZHOU Xiang

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1. College of Aerospace Science, National University of Defense Technology, Changsha 410073, China;
2. Beijing Institute of Astronautical Systems Engineering, Beijing 100076, China;
3. College of Science, Beijing Jiaotong University, Beijing 100093, China

Received date: 2020-07-04

Revised date: 2020-07-26

Online published: 2020-09-14

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摘要

从高超声速飞行器集群"探测-打击-评估"一体化任务需求出发，针对多滑翔飞行器时间协同再入轨迹规划问题进行研究，提出集群再入的协同形式及轨迹规划方案，基于改进序列凸化算法解决了再入总飞行时间的精确控制问题，从而实现滑翔段时间协同。首先，给出了滑翔飞行器集群的协同策略，将求解模型转化为协同时间的确定、协同时间约束下的轨迹规划子问题。将模型中的时间项误差等加入罚函数，提高了协同轨迹求解可行性。引入飞行路径角预设剖面作为软约束，并通过罚函数与信赖域自适应调整，以避免轨迹求解时的振荡问题，提高了序列凸化算法的收敛性。以CAV-H飞行器模型为例验证了算法的有效性，仿真结果表明，所提算法对初值的敏感性低，求解得到的再入总时间可调范围与伪谱法一致，轨迹规划结果的平滑性及计算时间均优于伪谱法。

关键词： 再入轨迹规划; 时间协同; 凸优化; 罚函数; 信赖域

本文引用格式

刘哲 , 陆浩然 , 郑伟 , 闻国光 , 王奕迪 , 周祥 . 多滑翔飞行器时间协同轨迹快速规划[J]. 航空学报, 2021 , 42(11) : 524497 -524497 . DOI: 10.7527/S1000-6893.2020.24497

Abstract

Based on the requirement of "detection-attack-assessment" integrated mission of the hypersonic vehicle cluster, this paper studies the time-coordination reentry trajectory planning of multi-glide vehicles, proposes the cooperative form and planning scheme of the reentry cluster, and solves the precise control problem of the total reentry flight time based on the improved sequential convex programming algorithm, thereby realizing the time-coordination of the glide cluster. The cooperative scheme of the glide cluster is firstly presented, and the solution model transformed into the sub problems of the determination of coordinated time and trajectory planning with the coordinated time constraint. The terminal time error is added to the penalty function to improve the calculation feasibility of the cooperative trajectory. The flight path angle preset profile is introduced as a soft constraint, with the penalty function and trust region adaptively adjusted to avoid the oscillation problem of trajectory solution and improve the convergence of sequential convex programming algorithm. The effectiveness of the proposed method is verified by the CAV-H model. The simulation results show that the adjustable range of the total reentry time obtained by the convex algorithm is consistent with the pseudospectral method, and the smoothness and calculation time of the trajectory planning results are better than those of the pseudospectral method.

Key words： reentry trajectory planning; time coordination; convex optimization; penalty function; trust region

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