In this paper, we propose an adaptive control approach to deal with the problems of input saturation, external disturbances, and uncertainty in the unmanned autonomous helicopter system. The dynamics of the system take into account the presence of input saturation, uncertainty, and external disturbances. Auxiliary systems are built to handle the input saturation. The neural networks are applied to approximate the uncertain terms. The control scheme combining integral backstepping and sliding mode control is developed in position and attitude subsystems, respectively. In the closed-loop system, the boundedness of the signals is proved by means of the Lyapunov theory. The simulation demonstrates that the approach has good robustness and tracking performance.


    Access

    Download


    Export, share and cite



    Title :

    Integral Backstepping Sliding Mode Control for Unmanned Autonomous Helicopters Based on Neural Networks


    Contributors:
    Min Wan (author) / Mou Chen (author) / Mihai Lungu (author)


    Publication date :

    2023




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown




    Fuzzy integral sliding mode based on backstepping control synthesis for an autonomous helicopter

    Meguenni, Kadda Zemalache / Tahar, M / Benhadria, MR et al. | SAGE Publications | 2013




    Model predictive control for autonomous unmanned helicopters

    Joelianto, Endra / Maryami Sumarjono, Edwina / Budiyono, Agus et al. | Emerald Group Publishing | 2011


    Model predictive control for autonomous unmanned helicopters

    Joelianto, Endra | Online Contents | 2011