空天飞行器姿态直接力/气动力复合控制
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  • 英文篇名:Attitude Blended Control for Aerospace Vehicle with Lateral Thrusters and Aerodynamic Fins
  • 作者:李爱军 ; 王瑜 ; 郭永 ; 王长青
  • 英文作者:LI Aijun;WANG Yu;GUO Yong;WANG Changqing;School of Automation, Northwestern Polytechnical University;
  • 关键词:神经网络 ; 有限时间控制 ; 控制分配 ; 反推力系统 ; 复合控制
  • 英文关键词:neural network;;finite-time control;;control allocation;;reaction control system;;blended control;;aerospace vehicle;;sliding mode control;;simulation
  • 中文刊名:XBGD
  • 英文刊名:Journal of Northwestern Polytechnical University
  • 机构:西北工业大学自动化学院;
  • 出版日期:2019-06-15
  • 出版单位:西北工业大学学报
  • 年:2019
  • 期:v.37;No.177
  • 基金:航空科学基金(20160153003,2016ZC53019);; 中央高校基本科研业务费专项基金(3102017OQD026)资助
  • 语种:中文;
  • 页:XBGD201903014
  • 页数:9
  • CN:03
  • ISSN:61-1070/T
  • 分类号:107-115
摘要
针对空天飞行器再入段姿态控制问题,根据神经网络、滑模控制理论和控制分配技术,提出了一种有限时间复合控制策略。首先,根据空天飞行器再入段姿态模型设计了一种有限时间收敛的神经网络滑模控制器,得到使姿态角误差有限时间收敛的虚拟控制力矩。其次,采用控制分配技术将期望控制力矩映射到气动舵面和反推力系统。最后,通过对直接力/气动力复合控制的空天飞行器的仿真研究,验证了所提出复合控制策略的有效性。
        A finite-time blended control strategy is proposed for the reentry phase attitude control of the aerospace vehicle(ASV) based on the neural network, sliding mode control theory and control allocation. Firstly, a finite-time neural networks sliding mode controller is designed based on the attitude model of the ASV in the reentry phase to obtain the virtual control moments which can make the attitude error converge to the equilibrium point in finite time. Secondly, the desired control moments are mapped into the control commands on the aerodynamic deflectors and the reaction control system(RCS) by using the control allocation. Finally, simulation results are provided to demonstrate the effectiveness of the attitude blended control strategy proposed.
引文
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