Trajectory Tracking of a Quadcopter Using Fuzzy Logic and Neural Network Controllers

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dc.authoridCelen, Burak/0000-0001-6790-3704|Oniz, Yesim/0000-0002-8337-7852
dc.contributor.authorCelen, Burak
dc.contributor.authorOniz, Yesim
dc.date.accessioned2024-07-18T20:50:56Z
dc.date.available2024-07-18T20:50:56Z
dc.date.issued2018
dc.departmentİstanbul Bilgi Üniversitesien_US
dc.description6th International Conference on Control Engineering and Information Technology (CEIT) -- OCT 25-27, 2018 -- Istanbul, TURKEYen_US
dc.description.abstractIn this work, the trajectory tracking control of an Unmanned Aerial Vehicle (UAV) has been realised using fuzzy logic and neural network based controllers. Parrot AR.Drone 2.0 has been selected as the test platform. For simulated and real-time experimental studies, a square shaped reference trajectory has been generated, and the discrepancies from this trajectory in x-and y-directions along with their derivatives have been employed as the input signals to the proposed controllers. The update rules for the neural network have been derived based on the variable structure systems theory to enable stable online tuning of the parameters. The obtained results indicate that both fuzzy logic and neural network controllers can be applied effectively to the trajectory tracking of a drone, and particularly neural networks with variable structure systems theory based learning algorithms exhibit a highly robust behaviour against disturbances.en_US
dc.description.sponsorshipYildiz Tech Univen_US
dc.identifier.isbn978-1-5386-7641-7
dc.identifier.scopus2-s2.0-85069209487en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://hdl.handle.net/11411/8293
dc.identifier.wosWOS:000491282100067en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartof2018 6th International Conference on Control Engineering & Information Technology (Ceit)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.titleTrajectory Tracking of a Quadcopter Using Fuzzy Logic and Neural Network Controllers
dc.typeConference Object

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