Real-time neural-network midcourse guidance

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The approximation capability of artificial neural networks has been applied to the midcourse guidance problem to overcome the difficulty of deriving an on-board guidance algorithm based on optimal control theory. This approach is to train a neural network to approximate the optimal guidance law in feedback form using the optimal trajectories computed in advance, Then the trained network is suitable for real-Lime implementation as well as generating suboptimal commands. In this paper, the advancement of the neural-network approach to the current level from the design procedure to the three-dimensional flight is described. (C) 2001 Published by Elsevier Science Ltd.
Publisher
PERGAMON-ELSEVIER SCIENCE LTD
Issue Date
2001-10
Language
English
Article Type
Article
Keywords

TO-AIR MISSILES; TRAJECTORY-SHAPING GUIDANCE

Citation

CONTROL ENGINEERING PRACTICE, v.9, no.10, pp.1145 - 1154

ISSN
0967-0661
DOI
10.1016/S0967-0661(01)00058-2
URI
http://hdl.handle.net/10203/84151
Appears in Collection
AE-Journal Papers(저널논문)
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