摘要
为解决运载火箭推力下降时无法正常入轨的问题,基于局部配点法和神经网络提出了入轨能力评估与轨迹重构方法。首先,采用局部配点法求解燃耗最优入轨问题,离线生成不同推力下降故障时运载火箭进入目标轨道和次级轨道的轨迹数据库。然后,采用神经网络学习轨迹数据库,建立推力下降故障与入轨能力之间的映射关系,从而使运载火箭出现推力下降时能对入轨能力在线评估与决策。最后,采用局部配点法进行在线轨迹重构,实现运载火箭入轨。数值仿真结果表明,本文方法可实现运载火箭推力下降时入轨能力评估和在线轨迹重构,从而提高发射任务的成功率。
To avoid the failure of orbit insertion caused by thrust decline,a mission capability evaluation and trajectory reconstruction method is proposed based on the local collocation method and neural network.First,the local collocation method is used to solve the fuel-optimal launch ascent problem,leading to the establishment of the trajectory database for the target and secondary rescue orbit insertion scenarios with various thrust decline percentages.Then,the mapping between the thrust decline percentage and the mission capability is learned from the trajectory database by using the neural network.Thus,the mission capability evaluation and decision can be made in real time when the thrust declines.As last,the online trajectory reconstruction is carried out using the local collocation method to perform the orbit insertion.Numerical simulation results show that the proposed method can evaluate the mission capability and reconstruct the ascent trajectory when the thrust of the launch vehicle declines,thereby improving the success rate of the launch mission.
作者
李爽
林子瑞
叶松
刘旭
赵吉松
LI Shuang;LIN Zi-rui;YE Song;LIU Xu;ZHAO Ji-song(College of Astronautics,Nanjing University of Aeronautics and Astronautics,Nanjing 211106,China;Beijing Aerospace Automatic Control Institute,Beijing 100854,China)
出处
《吉林大学学报(工学版)》
EI
CAS
CSCD
北大核心
2023年第8期2245-2253,共9页
Journal of Jilin University:Engineering and Technology Edition
基金
国家自然科学基金项目(11672126,61273051)
航天一院高校联合创新基金项目(CALT201703).
关键词
运载火箭
轨迹重构
推力下降
神经网络
局部配点法
launch vehicle
trajectory reconstruction
thrust decline
neural networks
local collocation method