吉林大学学报(工学版) ›› 2023, Vol. 53 ›› Issue (8): 2245-2253.doi: 10.13229/j.cnki.jdxbgxb.20211120

• 车辆工程·机械工程 • 上一篇    

运载火箭推力下降时入轨能力评估与轨迹重构方法

李爽1(),林子瑞1,叶松2,刘旭1,赵吉松1   

  1. 1.南京航空航天大学 航天学院,南京 211106
    2.北京航天自动控制研究所,北京 100854
  • 收稿日期:2021-10-28 出版日期:2023-08-01 发布日期:2023-08-21
  • 作者简介:李爽(1978-),男,教授,博士. 研究方向:深空探测、航天器动力学与控制技术.E-mail: lishuang@nuaa.edu.cn
  • 基金资助:
    国家自然科学基金项目(11672126);航天一院高校联合创新基金项目(CALT201703)

Orbital capability evaluation and trajectory reconstruction for launch vehicle with thrust decline

Shuang LI1(),Zi-rui LIN1,Song YE2,Xu LIU1,Ji-song ZHAO1   

  1. 1.College of Astronautics,Nanjing University of Aeronautics and Astronautics,Nanjing 211106,China
    2.Beijing Aerospace Automatic Control Institute,Beijing 100854,China
  • Received:2021-10-28 Online:2023-08-01 Published:2023-08-21

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。

关键词: 运载火箭, 轨迹重构, 推力下降, 神经网络, 局部配点法

Abstract:

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.

Key words: launch vehicle, trajectory reconstruction, thrust decline, neural networks, local collocation method

中图分类号: 

  • V488.23

图1

运载火箭推力下降示意图"

图2

推力故障下的入轨能力评估与决策方案"

图3

局部配点法标称轨迹"

图4

推力下降后的故障容许极限"

图5

助推级推力下降时进入次级轨道的故障容许极限"

图6

芯级发动机推力下降时进入次级轨道的故障容许极限"

图7

芯级发动机400 s时推力下降后进入次级轨道"

图8

推力下降数据库的最优平方差迭代曲线"

表1

芯级发动机推力线性下降仿真参数"

故障发生时刻t/s故障比例系数kCl次级轨道高度rf/km
500.686578
1500.776678
2500.836778
3500.846900

表2

芯级发动机推力比例下降仿真参数"

故障发生时刻t/s故障比例系数kCk次级轨道高度rf/km
500.786578
2000.866678
2500.906778
3500.916900

图9

芯级发动机推力下降后轨迹重构"

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