Multiconstrained Real-Time Entry Guidance Using Deep Neural Networks

In this article, an intelligent predictor-corrector entry guidance approach for lifting hypersonic vehicles is proposed to achieve real-time and safe control of entry flights by leveraging the deep neural network (DNN) and constraint management techniques. First, the entry trajectory planning proble...

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Veröffentlicht in:	IEEE transactions on aerospace and electronic systems Jg. 57; H. 1; S. 325 - 340
Hauptverfasser:	Cheng, Lin, Jiang, Fanghua, Wang, Zhenbo, Li, Junfeng
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.02.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Aerodynamics Algorithms Approximation algorithms Artificial neural networks Constraint management deep neural networks (DNNs) Earth entry guidance Hypersonic vehicles lateral heading control Neural networks numerical predictor–corrector guidance (NPCG) Prediction algorithms Predictor-corrector methods Real time Real-time systems Terminal constraints Trajectory Trajectory planning Vehicle dynamics
ISSN:	0018-9251, 1557-9603
Online-Zugang:	Volltext
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