Trajectory Control of Quadrotors via Spiking Neural Networks

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dc.authorid0000-0002-8337-7852
dc.contributor.authorOniz, Yesim
dc.date.accessioned2026-04-04T18:56:07Z
dc.date.available2026-04-04T18:56:07Z
dc.date.issued2024
dc.departmentİstanbul Bilgi Üniversitesi
dc.description.abstractIn this study, a novel control scheme based on spiking neural networks (SNNs) has been proposed to accomplish the trajectory tracking of quadrotor unmanned aerial vehicles (UAVs). The update rules for the network parameters have been derived using the Lyapunov stability theorem. Three different trajectories have been utilized in the simulated and experimental studies to verify the efficacy of the proposed control scheme. The acquired results have been compared with the responses obtained for proportional-integral-derivative (PID) and traditional neural network controllers. Simulated and experimental studies demonstrate that the proposed SNN-based controller is capable of providing better tracking accuracy and robust system response in the presence of disturbing factors.
dc.description.sponsorshipBilgi Research Fund of Istanbul Bilgi University; [AK 850890000]
dc.description.sponsorshipThis research was funded by the Bilgi Research Fund of Istanbul Bilgi University (Project no: AK 850890000).
dc.identifier.doi10.3390/electronics13163319
dc.identifier.doi10.3390/electronics13163319
dc.identifier.issn2079-9292
dc.identifier.issue16
dc.identifier.scopus2-s2.0-85202698586
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.3390/electronics13163319
dc.identifier.urihttps://hdl.handle.net/11411/10695
dc.identifier.volume13
dc.identifier.wosWOS:001305070600001
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherMdpi
dc.relation.ispartofElectronics
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_WoS_20260402
dc.snmzKA_Scopus_20260402
dc.subjectRotary Wing Unmanned Aerial Vehicle
dc.subjectSpiking Neural Networks
dc.subjectTrajectory Tracking
dc.titleTrajectory Control of Quadrotors via Spiking Neural Networks
dc.typeArticle

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