Missile guidance using neural networks

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This paper introduces a new guidance algorithm using neural networks for bank-to-turn (BTT) missiles. The proposed guidance algorithm compensates for the missile dynamics by using the inverse dynamics learned by neural networks. The new guidance law is applied to a full-order nonlinear BTT missile model, and the performance is compared with that of the proportional navigation guidance law. Copyright (C) 1997 Elsevier Science Ltd.
Publisher
PERGAMON-ELSEVIER SCIENCE LTD
Issue Date
1997-06
Language
English
Article Type
Article
Citation

CONTROL ENGINEERING PRACTICE, v.5, no.6, pp.753 - 762

ISSN
0967-0661
URI
http://hdl.handle.net/10203/76210
Appears in Collection
AE-Journal Papers(저널논문)
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