宇航学报 ›› 2021, Vol. 42 ›› Issue (2): 175-184.doi: 10.3873/j.issn.1000-1328.2021.02.005

• 制导、导航、控制与电子 • 上一篇    下一篇

空天飞行器返回滑翔段在线制导方法

周宏宇,王小刚,赵亚丽,崔乃刚   

  1. 1. 哈尔滨工业大学航天学院,哈尔滨 1500012. 北京航天晨信科技有限公司,北京 102308
  • 收稿日期:2020-03-14 修回日期:2020-04-27 出版日期:2021-02-15 发布日期:2021-02-15
  • 基金资助:
    中国博士后科学基金(2019M661290)

Online Guidance for Aerospace Vehicle in Return Gliding Phase

ZHOU Hong yu, WANG Xiao gang, ZHAO Ya li, CUI Nai gang   

  1. 1. School of Astronautics, Harbin Institute of Technology, Harbin 150001, China;2. Beijing Aerocim Technology Co., Ltd, Beijing 102308, China
  • Received:2020-03-14 Revised:2020-04-27 Online:2021-02-15 Published:2021-02-15

摘要: 针对空天往返飞行器的返回滑翔段在线制导问题,设计了一种新的滑翔段飞行剖面,实现了滑翔段终端交班高度、位置和倾角约束的自动满足,减少了在线制导算法中需处理的约束数量。推导了滑翔段运动状态、过程约束和性能指标的解析表达式,获得了剩余航程和终端速度间的函数关系。在此基础上,提出了一种双层在线制导方法:内层解析重构飞行剖面,同时通过解析确定路径点来改变剩余航程的变化率,进而对终端交班速度进行控制;外层借助解析表达式,使用粒子群优化算法(PSO)和改进共轭梯度法(CGM)优化飞行剖面,从而满足过程约束和指标要求。最后通过数学仿真验证了方法的正确性。

关键词: 空天飞行器, 返回滑翔, 在线制导, 解析动力学, 优化算法

Abstract: This paper studies the online gliding guidance law for aerospace vehicles in the return phase. A new flight profile in the gliding phase is proposed initially, according to which the constraints on the altitude, the heading angle, the flight path angle and the range to go that are necessary for smooth transition to the terminal area energy management, can be automatically satisfied, thus reducing the number of constraints addressed in the guidance law. The accurate analytical solutions in the gliding phase are deduced. In addition, the analytical expressions of the path constraints and the performance indexes are obtained, and the dissipation in the velocity is analytically represented with respect to the range to go. Then a double loop guidance law is proposed based on these analytical expressions. In order to meet the terminal velocity, the inner loop revises the profile analytically and controls the range to go by determining the waypoint. In order to satisfy the path constraints and optimize the trajectory, the outer loop optimizes the profile with a particle swarm optimization method and an improved conjugate gradient method with analytical expressions. Finally, the numerical simulation demonstrates the effectiveness of the proposed online guidance law.

Key words: Aerospace vehicle, Reentry gliding, Online guidance; Analytical dynamics, Optimization algorithm

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