系统工程与电子技术 ›› 2023, Vol. 45 ›› Issue (8): 2570-2577.doi: 10.12305/j.issn.1001-506X.2023.08.32

• 制导、导航与控制 • 上一篇    下一篇

重型运载火箭预设时间自适应控制

姜雨石1,*, 陈旸1, 高路1, 蔡李根1, 吕吉星2   

  1. 1. 北京航天长征飞行器研究所, 北京 100076
    2. 哈尔滨工业大学航天学院, 黑龙江 哈尔滨 150006
  • 收稿日期:2022-04-06 出版日期:2023-07-25 发布日期:2023-08-03
  • 通讯作者: 姜雨石
  • 作者简介:姜雨石 (1997—), 男, 工程师, 硕士, 主要研究方向为飞行器姿态控制
    陈旸 (1977—), 男, 高级工程师, 硕士, 主要研究方向为飞行器总体设计
    高路 (1981—), 男, 研究员, 博士, 主要研究方向为飞行器总体设计
    蔡李根 (1995—), 男, 工程师, 硕士, 主要研究方向为飞行器姿态控制
    吕吉星 (1997—), 男, 博士研究生, 主要研究方向为飞行器姿态控制

Predefined-time adaptive control for heavy-lift launch vehicles

Yushi JIANG1,*, Yang CHEN1, Lu GAO1, Ligen CAI1, Jixing LYU2   

  1. 1. Beijing Institute of Space Long March Vehicle, Beijing 100076, China
    2. School of Astronautics, Harbin Institute of Technology, Harbin 150006, China
  • Received:2022-04-06 Online:2023-07-25 Published:2023-08-03
  • Contact: Yushi JIANG

摘要:

针对存在模型不确定性及未知外部干扰的重型运载火箭姿态控制问题, 提出一种新型预设时间自适应控制方法, 使得姿态控制误差收敛时间与系统初始状态无关且可预先设定。首先设计一种新型预设时间滑模面, 采用滑模面切换的方法避免系统出现奇异; 然后设计预设时间滑模控制器, 采用神经网络估计系统集总扰动并在控制器中进行补偿, 设计自适应律自适应调整神经网络权重系数, 基于Lyapunov稳定性定理证明了所设计控制器的预设时间稳定性; 最后通过数值仿真验证了所提方法的可行性及有效性。

关键词: 重型运载火箭, 预设时间滑模面, 预设时间滑模控制, 神经网络, 自适应律

Abstract:

In view of the attitude control problem of the heavy-lift launch vehicle with model uncertainty and unknown external interference, a novel predefined-time adaptive control method is proposed, which makes the convergence time of attitude control errors is independent of any system initial condition and can be preset. Firstly, a novel predefined-time sliding mode surface is designed, and the sliding mode surface switching method is used to avoid the singularity. Secondly, a predefined-time sliding mode controller is designed. The lumped disturbance of the system is estimated by neural network and compensated in the controller, and the adaptive law is designed to adaptively adjust the weight coefficient of neural network. The predefined-time stability of the designed controller is proved based on Lyapunov stability theorem. Finally, the feasibility and effectiveness of the proposed method is verified by numerical simulations.

Key words: heavy-lift launch vehicle, predefined-time sliding mode surface, predefined-time sliding mode control, neural network, adaptive law

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