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  • MakaleAçık Erişim2022Scopus SJRQ1
    Finite-Time Neuro-Sliding-Mode Controller Design for Quadrotor UAVs Carrying Suspended Payload

    Bingöl, Özhan; Güzey, Hacı Mehmet

    Due to the quadrotor’s underactuated nature, suspended payload dynamics, parametric uncertainties, and external disturbances, designing a controller for tracking the desired trajectories for a quadrotor that carries a suspended payload is a challenging task. Furthermore, one of the most significant disadvantages of designing a controller for nonlinear systems is the infinite-time convergence to the desired trajectory. In this paper, a finite-time neuro-sliding mode controller (FTNSMC) for a quadrotor with a suspended payload that is subject to parametric uncertainties and external disturbances is designed. By constructing a finite-time sliding mode controller, the quadrotor can follow the reference trajectories in finite time. Furthermore, despite time-varying nonlinear dynamics, parametric uncertainties, and external disturbances, a neural network structure is added to the controller to effectively reduce chattering phenomena caused by high switching gains, and significantly reduce the size of the control signals. Following the completion of the controller design, the system’s stability is demonstrated using the Lyapunov stability criterion. Extensive numerical simulations with various scenarios are run to demonstrate the effectiveness of the proposed controller.

    AtıfScopus28WoS22OpenAlex21
    ScopusWeb of Scienceİncele
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AlanDeğerDil
creativeworkseries.issn2504-446X
dc.date.accessioned2026-10-22T10:19:22.357126394Z
dc.date.available2026-10-22T10:19:22.357126394Z
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/gumushane/11790
dc.publisherMultidisciplinary Digital Publishing Institute (MDPI)
dc.rightsinfo:eu-repo/semantics/openAccess
dc.titleDrones