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請用此 Handle URI 來引用此文件: http://scholars.ntou.edu.tw/handle/123456789/18066
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dc.contributor.authorJih-Gau Juangen_US
dc.contributor.authorLi-Hsiang Chienen_US
dc.date.accessioned2021-10-28T07:30:55Z-
dc.date.available2021-10-28T07:30:55Z-
dc.date.issued2010-
dc.identifier.isbn978-3-642-16692-1-
dc.identifier.urihttp://scholars.ntou.edu.tw/handle/123456789/18066-
dc.description.abstractThis paper presents an intelligent automatic landing system that uses adaptive fuzzy neural network controller to improve the performance of conventional automatic landing systems. Functional fuzzy rules are implemented in neural network. In this study, Lyapunov stability theory is utilized to derive adaptive learning rate in the controller design. Stability of the control system is guaranteed. Simulation results show that the fuzzy neural network controller with adaptive learning rate has better performance than PID controller in guiding aircraft to a safe landing in turbulence condition.en_US
dc.language.isoenen_US
dc.relation.ispartofLecture Notes in Artificial Intelligenceen_US
dc.titleAdaptive Fuzzy Neural Network Control for Automatic Landing Systemen_US
dc.typejournal articleen_US
dc.identifier.doi10.1007/978-3-642-16693-8_53-
dc.relation.journalvolume6421en_US
dc.relation.pages520-530en_US
item.fulltextno fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.cerifentitytypePublications-
item.grantfulltextnone-
item.languageiso639-1en-
item.openairetypejournal article-
crisitem.author.deptCollege of Electrical Engineering and Computer Science-
crisitem.author.deptDepartment of Communications, Navigation and Control Engineering-
crisitem.author.deptNational Taiwan Ocean University,NTOU-
crisitem.author.parentorgNational Taiwan Ocean University,NTOU-
crisitem.author.parentorgCollege of Electrical Engineering and Computer Science-
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