Real-time midcourse guidance with intercept point prediction

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dc.contributor.authorSong, EJko
dc.contributor.authorTahk, Min-Jeako
dc.date.accessioned2013-03-02T16:48:42Z-
dc.date.available2013-03-02T16:48:42Z-
dc.date.created2012-02-06-
dc.date.created2012-02-06-
dc.date.issued1998-08-
dc.identifier.citationCONTROL ENGINEERING PRACTICE, v.6, no.8, pp.957 - 967-
dc.identifier.issn0967-0661-
dc.identifier.urihttp://hdl.handle.net/10203/74526-
dc.description.abstractIn 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.-
dc.languageEnglish-
dc.publisherPERGAMON-ELSEVIER SCIENCE LTD-
dc.subjectTO-AIR MISSILES-
dc.titleReal-time midcourse guidance with intercept point prediction-
dc.typeArticle-
dc.identifier.wosid000077551600004-
dc.identifier.scopusid2-s2.0-0032131110-
dc.type.rimsART-
dc.citation.volume6-
dc.citation.issue8-
dc.citation.beginningpage957-
dc.citation.endingpage967-
dc.citation.publicationnameCONTROL ENGINEERING PRACTICE-
dc.contributor.localauthorTahk, Min-Jea-
dc.contributor.nonIdAuthorSong, EJ-
dc.type.journalArticleArticle-
dc.subject.keywordAuthormidcourse guidance-
dc.subject.keywordAuthorsuboptimal feedback law-
dc.subject.keywordAuthoroptimal trajectory-
dc.subject.keywordAuthorneural networks-
dc.subject.keywordAuthoriterative prediction algorithms-
dc.subject.keywordPlusTO-AIR MISSILES-
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