Real-time midcourse guidance with intercept point prediction

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In this paper, an on-line suboptimal midcourse guidance law, which is a neural-network approximation of the optimal feedback strategy, is proposed to eliminate the need for solving two-point boundary-value problems in real time. Moreover, for intercept point prediction, a fast converging, iterative algorithm based on a neural network time-to-go estimator is devised. Computer simulations confirm that the closed-loop behavior of the proposed guidance law is so close to the optimal trajectory that it outperforms nonoptimal guidance laws such as g-biased proportional navigation. (C) 1998 Elsevier Science Ltd. All rights reserved.
Publisher
PERGAMON-ELSEVIER SCIENCE LTD
Issue Date
1998-08
Language
English
Article Type
Article
Keywords

TO-AIR MISSILES

Citation

CONTROL ENGINEERING PRACTICE, v.6, no.8, pp.957 - 967

ISSN
0967-0661
URI
http://hdl.handle.net/10203/74526
Appears in Collection
AE-Journal Papers(저널논문)
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