An adaptive event-triggered trajectory tracking control approach is designed to address parameter uncertainties and external disturbance in quadrotor unmanned aerial vehicle (UAV) systems. Combine backstepping method with dynamic surface control method. Introduce radial basis function neural network (RBFNN) to compensate for unknown disturbance. Propose an event-triggered mechanism to reduce update frequency, thereby reducing actuator wear. Simulation results demonstrate that this control method has strong anti-interference ability and achieves ideal control accuracy, effectively solving the double-closed-loop trajectory tracking control problem of quadrotor UAVs.


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    Titel :

    Event-Triggered Adaptive Trajectory Tracking Control for Quadrotor Unmanned Aerial Vehicles


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Deng, Zhidong (Herausgeber:in) / Zhao, Zhongyuan (Autor:in) / Cao, Chengjie (Autor:in) / Luo, Zijuan (Autor:in)

    Kongress:

    Chinese Intelligent Automation Conference ; 2023 ; Nanjing, China October 02, 2023 - October 05, 2023



    Erscheinungsdatum :

    23.09.2023


    Format / Umfang :

    8 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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