DC Field | Value | Language |
---|---|---|
dc.contributor.author | Song, EJ | ko |
dc.contributor.author | Tahk, Min-Jea | ko |
dc.date.accessioned | 2013-03-04T21:09:53Z | - |
dc.date.available | 2013-03-04T21:09:53Z | - |
dc.date.created | 2012-02-06 | - |
dc.date.created | 2012-02-06 | - |
dc.date.issued | 2001-10 | - |
dc.identifier.citation | CONTROL ENGINEERING PRACTICE, v.9, no.10, pp.1145 - 1154 | - |
dc.identifier.issn | 0967-0661 | - |
dc.identifier.uri | http://hdl.handle.net/10203/84151 | - |
dc.description.abstract | 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. | - |
dc.language | English | - |
dc.publisher | PERGAMON-ELSEVIER SCIENCE LTD | - |
dc.subject | TO-AIR MISSILES | - |
dc.subject | TRAJECTORY-SHAPING GUIDANCE | - |
dc.title | Real-time neural-network midcourse guidance | - |
dc.type | Article | - |
dc.identifier.wosid | 000171242900010 | - |
dc.identifier.scopusid | 2-s2.0-0035478628 | - |
dc.type.rims | ART | - |
dc.citation.volume | 9 | - |
dc.citation.issue | 10 | - |
dc.citation.beginningpage | 1145 | - |
dc.citation.endingpage | 1154 | - |
dc.citation.publicationname | CONTROL ENGINEERING PRACTICE | - |
dc.identifier.doi | 10.1016/S0967-0661(01)00058-2 | - |
dc.contributor.localauthor | Tahk, Min-Jea | - |
dc.contributor.nonIdAuthor | Song, EJ | - |
dc.type.journalArticle | Article | - |
dc.subject.keywordAuthor | midcourse guidance | - |
dc.subject.keywordAuthor | suboptimal guidance | - |
dc.subject.keywordAuthor | neural networks | - |
dc.subject.keywordAuthor | feedback form | - |
dc.subject.keywordAuthor | optimal trajectory | - |
dc.subject.keywordPlus | TO-AIR MISSILES | - |
dc.subject.keywordPlus | TRAJECTORY-SHAPING GUIDANCE | - |
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