首页|Deep reinforcement learning guidance with impact time control

Deep reinforcement learning guidance with impact time control

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In consideration of the field-of-view(FOV)angle con-straint,this study focuses on the guidance problem with impact time control.A deep reinforcement learning guidance method is given for the missile to obtain the desired impact time and meet the demand of FOV angle constraint.On basis of the framework of the proportional navigation guidance,an auxiliary control term is supplemented by the distributed deep deterministic policy gradient algorithm,in which the reward functions are developed to decrease the time-to-go error and improve the terminal guid-ance accuracy.The numerical simulation demonstrates that the missile governed by the presented deep reinforcement learning guidance law can hit the target successfully at appointed arrival time.

impact timedeep reinforcement learningguidance lawfield-of-view(FOV)angledeep deterministic policy gradient

LI Guofei、LI Shituo、LI Bohao、WU Yunjie

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School of Astronautics,Northwestern Polytechnical University,Xi'an 710072,China

Beijing Institute of Control and Electronic Technology,Beijing 100038,China

School of Automation Science and Electrical Engineering,Beihang University,Beijing 100191,China

2024

系统工程与电子技术(英文版)
中国航天科工防御技术研究院 中国宇航学会 中国系统工程学会 中国系统仿真学会

系统工程与电子技术(英文版)

CSTPCD
影响因子:0.64
ISSN:1004-4132
年,卷(期):2024.35(6)