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dc.contributor.authorWang, Chi-Hsuen_US
dc.contributor.authorHung, Kun-Nengen_US
dc.date.accessioned2014-12-08T15:32:06Z-
dc.date.available2014-12-08T15:32:06Z-
dc.date.issued2013-06-01en_US
dc.identifier.issn1562-2479en_US
dc.identifier.urihttp://hdl.handle.net/11536/22615-
dc.description.abstractIn this paper, an adaptive fuzzy neural network (FNN) controller is proposed for missile guidance. The objective is for one defending missile (DM) to intercept an attacking missile (AM) in air battle scenario. The adaptive FNN controller is adopted to force the DM toward the AM under the existence of disturbance, and a monitoring controller is also designed to reduce the error between FNN controller and ideal controller. In comparison with the other multi-layered neural network controller, the proposed adaptive FNN controller which combines the fuzzy rules with the neural network can be easily designed. The weighting factors of our new FNN controller are activated to dispatch the DM toward the AM. Using the Lyapunov constraints, the weighting factors for the proposed FNN controller are updated to guarantee the stability of the path planning system. In our illustrated examples, the systematic battle environment is constructed. From the simulation results, the proposed adaptive FNN controller is capable of performing missile guidance, and it also shows that the computation load of our proposed approach is much less than that of using cerebellar model articulation controller (CMAC).en_US
dc.language.isoen_USen_US
dc.subjectcommand line-of-sight (CLOS) guidance modelen_US
dc.subjectfuzzy neural network (FNN)en_US
dc.subjectLyapunov theoremen_US
dc.subjectmissile guidance lawen_US
dc.titleIntelligent Adaptive Law for Missile Guidance Using Fuzzy Neural Networksen_US
dc.typeArticleen_US
dc.identifier.journalINTERNATIONAL JOURNAL OF FUZZY SYSTEMSen_US
dc.citation.volume15en_US
dc.citation.issue2en_US
dc.citation.spage182en_US
dc.citation.epage191en_US
dc.contributor.department電機工程學系zh_TW
dc.contributor.departmentDepartment of Electrical and Computer Engineeringen_US
dc.identifier.wosnumberWOS:000322925500009-
dc.citation.woscount2-
Appears in Collections:Articles