微分博弈
非线性系统
控制理论(社会学)
导弹
导弹制导
微分动态规划
计算机科学
动态规划
差速器(机械装置)
人工神经网络
微分方程
李雅普诺夫函数
数学优化
数学
人工智能
控制(管理)
工程类
数学分析
物理
量子力学
航空航天工程
作者
A-xing Xi,Yuanli Cai,Yifan Deng,Haonan Jiang
标识
DOI:10.1177/09544100231191411
摘要
In this paper, for solving the nonlinear control problem of the missile intercepting the maneuvering target, a novel nonlinear zero-sum differential game guidance law is proposed via the neuro-dynamic programming approach. First, the continuous-time nonlinear differential game problem is transformed into solving the nonlinear Hamilton–Jacobi–Isaacs (HJI) equation. Then, a critic neural network is designed to solve the corresponding nonlinear HJI equation. An adaptive weight tuning law for the critic weights is proposed, where an additional term is added to ensure the stability of the closed-loop nonlinear system. Furthermore, the uniform ultimate boundedness of the closed-loop system and the critic NN weights estimation error are proved with the Lyapunov approach. Finally, some simulation results are presented to demonstrate the effectiveness of the proposed differential game guidance law for nonlinear interception.
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