典型文献
A DNN based trajectory optimization method for intercepting non-cooperative maneuvering spacecraft
文献摘要:
Current successes in artificial intelligence domain have revitalized interest in neural networks and demonstrated their potential in solving spacecraft trajectory optimization prob-lems. This paper presents a data-free deep neural network (DNN) based trajectory optimization method for intercepting non-cooperative maneuvering spacecraft, in a continuous low-thrust scenario. Firstly, the problem is formulated as a standard con-strained optimization problem through differential game theory and minimax principle. Secondly, a new DNN is designed to in-tegrate interception dynamic model into the network and involve it in the process of gradient descent, which makes the network endowed with the knowledge of physical constraints and re-duces the learning burden of the network. Thus, a DNN based method is proposed, which completely eliminates the demand of training datasets and improves the generalization capacity. Fi-nally, numerical results demonstrate the feasibility and efficiency of our proposed method.
文献关键词:
中图分类号:
作者姓名:
YANG Fuyunxiang;YANG Leping;ZHU Yanwei;ZENG Xin
作者机构:
College of Aerospace Science and Engineering,National University of Defense Technology,Changsha 410073,China
文献出处:
引用格式:
[1]YANG Fuyunxiang;YANG Leping;ZHU Yanwei;ZENG Xin-.A DNN based trajectory optimization method for intercepting non-cooperative maneuvering spacecraft)[J].系统工程与电子技术(英文版),2022(02):438-446
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AB值:
0.630624
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