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Xi Lyu, Yushan Sun, Lifeng Wang, Jiehui Tan and Liwen Zhang
This study aims to solve the problems of sparse reward, single policy, and poor environmental adaptability in the local motion planning task of autonomous underwater vehicles (AUVs). We propose a two-layer deep deterministic policy gradient algorithm-bas...
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Jovan Menezes and Timothy Sands
Discretization is the process of converting a continuous function or model or equation into discrete steps. In this work, learning and adaptive techniques are implemented to control DC motors that are used for actuating control surfaces of unmanned under...
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Hao Chen, Chuanqiang Gao, Jifei Wu, Kai Ren and Weiwei Zhang
Transonic buffet is a phenomenon of large self-excited shock oscillations caused by shock wave-boundary layer interaction, which is one of the common flow instability problems in aeronautical engineering. This phenomenon involves unsteady flow, which mak...
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Wanli Li, Jiong Li, Ningbo Li, Lei Shao and Mingjie Li
Concerned with the problem of interceptor midcourse guidance trajectory online planning satisfying multiple constraints, an online midcourse guidance trajectory planning method based on deep reinforcement learning (DRL) is proposed. The Markov decision p...
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Yunhe Guo, Zijian Jiang, Hanqiao Huang, Hongjia Fan and Weiye Weng
In order to improve the problem of overly relying on situational information, high computational power requirements, and weak adaptability of traditional maneuver methods used by hypersonic vehicles (HV), an intelligent maneuver strategy combining deep r...
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