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  • Active Full-Vehicle Suspension Control via Cloud-Aided Adaptive Backstepping Approach.

    Author(s)
    Zheng, X
    Zhang, H
    Yan, H
    Yang, F
    Wang, Z
    Vlacic, L
    Griffith University Author(s)
    Vlacic, Ljubo
    Yang, Fuwen
    Year published
    2020
    Metadata
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    Abstract
    This paper is concerned with the adaptive backstepping control problem for a cloud-aided nonlinear active full-vehicle suspension system. A novel model for a nonlinear active suspension system is established, in which uncertain parameters, unknown friction forces, nonlinear springs and dampers, and performance requirements are considered simultaneously. In order to deal with the nonlinear characteristics, a backstepping control strategy is developed. Meanwhile, an adaptive control strategy is proposed to handle the uncertain parameters and unknown friction forces. In the cloud-aided vehicle suspension system framework, the ...
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    This paper is concerned with the adaptive backstepping control problem for a cloud-aided nonlinear active full-vehicle suspension system. A novel model for a nonlinear active suspension system is established, in which uncertain parameters, unknown friction forces, nonlinear springs and dampers, and performance requirements are considered simultaneously. In order to deal with the nonlinear characteristics, a backstepping control strategy is developed. Meanwhile, an adaptive control strategy is proposed to handle the uncertain parameters and unknown friction forces. In the cloud-aided vehicle suspension system framework, the adaptive backstepping controller is updated in a remote cloud based on the cloud storing information, such as road information, vehicle suspension information, and reference trajectories. Finally, simulation results for a full vehicle with 7-degree of freedom model are provided to demonstrate the effectiveness of the proposed control scheme, and it is shown that the addressed controller can improve the performances more than 80% compared with passive vehicle suspension systems.
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    Journal Title
    IEEE Transactions on Cybernetics
    DOI
    https://doi.org/10.1109/TCYB.2019.2891960
    Subject
    Artificial intelligence
    Applied mathematics
    Electronics, sensors and digital hardware
    Publication URI
    http://hdl.handle.net/10072/384401
    Collection
    • Journal articles

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