系统工程与电子技术 ›› 2023, Vol. 45 ›› Issue (11): 3616-3623.doi: 10.12305/j.issn.1001-506X.2023.11.29

• 制导、导航与控制 • 上一篇    下一篇

基于微分对策的非仿射导弹学习滑模制导

高煜欣, 刘春生   

  1. 南京航空航天大学自动化学院, 江苏 南京 211106
  • 收稿日期:2022-06-09 出版日期:2023-10-25 发布日期:2023-10-31
  • 通讯作者: 刘春生
  • 作者简介:高煜欣(1991—), 男, 博士研究生, 主要研究方向为滑模控制、最优控制、自适应动态规划
    刘春生(1955—), 女, 教授, 博士, 主要研究方向为现代飞行器控制、最优控制、鲁棒控制
  • 基金资助:
    国家自然科学基金(61473147);国家自然科学基金(62003036);北京市自然科学基金(4214077)

Differential game-based learning sliding mode guidance for non-affine missile system

Yuxin GAO, Chunsheng LIU   

  1. College of Automation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
  • Received:2022-06-09 Online:2023-10-25 Published:2023-10-31
  • Contact: Chunsheng LIU

摘要:

针对具有非仿射形式的导弹截机动目标问题,研究了一类基于微分对策的非仿射学习滑模制导方法。首先, 构建辅助系统, 将制导系统转化为增广控制仿射形式; 针对目标未知机动造成的扰动项, 设计自适应滑模控制策略, 鲁棒匹配扰动部分的同时使系统状态沿着预设滑模面进入滑动模态运动。然后, 针对带有非匹配扰动部分的等效滑动模态系统, 利用评价网络在线学习最优微分对策控制策略, 使系统满足预设性能指标, 并通过Lyapunov方法证明闭环系统有界。最后, 仿真结果表明导弹能够成功拦截目标, 证明了所提制导律的有效性。

关键词: 非仿射导弹系统, 学习滑模制导, 目标未知机动, 微分对策

Abstract:

For the interception problem of maneuvering target by the missile with non-affine form, a class of differential game-based non-affine learning sliding mode guidance method is investigated. Firstly, an auxiliary system is constructed and the guidance model is converted into augmented control-affine form. For the disturbance caused by the unknown target maneuver, the adaptive sliding mode control strategy is designed to counteract the matched part and force the states to move along the predefined sliding surface. Then, for the equivalent sliding mode dynamic system, which contains unmatched part, the critic network is utilized to learn the optimal differential game control strategy and the predefined performance function is satisfied. The closed-loop system is proved to be bounded by Lyapunov theory. Finally, the simulation results indicate the target can be intercepted by the missile successfully and the proposed guidance law is verified to be effective.

Key words: non-affine missile system, learning sliding mode guidance, unknown target maneuver, differential game

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