Quadrotor unmanned aerial vehicle (UAV) have always been a difficult problem in the design of UAV controllers in the face of complex exogenous disturbances during autonomous flight. Focusing on this problem, this paper put forward a sliding mode control method which combined with radial basis function neural network (RBFNN). Firstly, based on the Newtonian Euler equation, the trajectory tracking problem of quadrotor UAV is transformed into altitude and attitude control problem, and then the corresponding dynamic equations are obtained. Secondly, the controllers are designed based on the second-order sliding mode manifold, in the meantime, the gusts and uncertain parameters in the control law are estimated by using RBFNN. Simulation results show the stability and performance advantages of the proposed method applied to UAV control system.


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    Title :

    Anti-Wind Resistance Quadrotor UAV Sliding Mode Controller Design Based on RBFNN


    Contributors:
    Chen, Yin (author) / Xiong, Jingjing (author)


    Publication date :

    2024-07-26


    Size :

    1412090 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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