Detailed Information

Cited 4 time in webofscience Cited 0 time in scopus
Metadata Downloads

Adaptive Integrated Guidance and Control Design for Automatic Landing of a Fixed Wing Unmanned Aerial Vehicle

Full metadata record
DC Field Value Language
dc.contributor.authorKim, Boo Min-
dc.contributor.authorKim, Ji Tae-
dc.contributor.authorKim, Byoung Soo-
dc.contributor.authorHa, Cheolgun-
dc.date.accessioned2022-12-27T01:37:17Z-
dc.date.available2022-12-27T01:37:17Z-
dc.date.issued2012-10-
dc.identifier.issn0893-1321-
dc.identifier.issn1943-5525-
dc.identifier.urihttps://scholarworks.gnu.ac.kr/handle/sw.gnu/21987-
dc.description.abstractThis paper presents an automatic landing control design using adaptive, integrated guidance and control (IGC) logic. The proposed IGC design uses a combination of an adaptive output feedback inversion and backstepping techniques. The problem is formulated as an adaptive output feedback control problem for a line-of-sight-based chasing flight configuration. The design objective is to regulate the relative distance between the aircraft and the moving reference point on a landing pattern and two bearing angles maintaining turn coordination. Adaptive neural networks are trained online with available measurements to compensate for inversion error as a result of unmodeled dynamics and modeling errors of the aircraft in the design process. In addition, a reference command trajectory for the automatic landing control is designed in a way that the aircraft follows the landing pattern regardless of its initial position. The automatic landing system using IGC logic is evaluated using a sophisticated six-degrees-of-freedom nonlinear simulation program with the approach and landing scenario. DOI: 10.1061/(ASCE)AS.1943-5525.0000172. (C) 2012 American Society of Civil Engineers.-
dc.format.extent11-
dc.language영어-
dc.language.isoENG-
dc.publisherASCE-AMER SOC CIVIL ENGINEERS-
dc.titleAdaptive Integrated Guidance and Control Design for Automatic Landing of a Fixed Wing Unmanned Aerial Vehicle-
dc.typeArticle-
dc.publisher.location미국-
dc.identifier.doi10.1061/(ASCE)AS.1943-5525.0000172-
dc.identifier.wosid000313240400003-
dc.identifier.bibliographicCitationJOURNAL OF AEROSPACE ENGINEERING, v.25, no.4, pp 490 - 500-
dc.citation.titleJOURNAL OF AEROSPACE ENGINEERING-
dc.citation.volume25-
dc.citation.number4-
dc.citation.startPage490-
dc.citation.endPage500-
dc.type.docTypeArticle-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalWebOfScienceCategoryEngineering, Aerospace-
dc.relation.journalWebOfScienceCategoryEngineering, Civil-
dc.subject.keywordPlusNEURAL-NETWORKS-
dc.subject.keywordPlusFLIGHT-
dc.subject.keywordAuthorAutomatic landing-
dc.subject.keywordAuthorNeural networks-
dc.subject.keywordAuthorOutput feedback-
dc.subject.keywordAuthorBackstepping-
Files in This Item
There are no files associated with this item.
Appears in
Collections
공학계열 > 기계항공우주공학부 > Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Altmetrics

Total Views & Downloads

BROWSE