The main control objective for the quad-rotor system is the attitude and position tracking control which is accomplished in this article using the backstepping fractional-order sliding mode control approach combined with the adaptive tuning based barrier function theory. The quad-rotor's dynamical model is obtained at the appearance of the disturbance that is entered to the quad-rotor system by an exterior force. Hence, the attitude and position tracking errors between the quad-rotor's actual states and their desired trajectory are defined. Afterward, the fractional-order sliding surfaces are defined to guarantee finite-time reachability of the defined tracking error. The designed fractional-order surface eases the control process due to the removal of the high-derivative of virtual controllers. Then, the extended adaptive barrier function laws named fractional-order-based adaptive barrier function laws are employed to eliminate the knowledge of the upper bounds of external disturbances. The Lyapunov theory concept mixed with the backstepping control strategy is used to demonstrate that the fractional-order sliding surface reaches the neighborhood of origin in the finite time. Finally, simulation results in various scenarios on the MATLAB/ Simulink environment are provided to show that the designed control procedure in this article is an efficient control technique to assure that attitude and position's trajectories of the quad-rotor system track desired trajectories properly in the existence of the external disturbances. Moreover, the designed method is compared to the existing method to validate the efficiency of the proposed method. Lastly, experimental results using the Speedgoat real-time target machine is implemented to assure validity of the recommended method.


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    Titel :

    Barrier Function-Based Backstepping Fractional-Order Sliding Mode Control for Quad-Rotor Unmanned Aerial Vehicle Under External Disturbances


    Beteiligte:
    Liu, Bowen (Autor:in) / Wang, Yingxun (Autor:in) / Mofid, Omid (Autor:in) / Mobayen, Saleh (Autor:in) / Khooban, Mohammad Hassan (Autor:in)


    Erscheinungsdatum :

    2024-02-01


    Format / Umfang :

    1641754 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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