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.

中文翻译：

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通过云辅助自适应反步方法进行主动整车悬架控制


本文研究云辅助非线性主动整车悬架系统的自适应反步控制问题。建立了一种新的非线性主动悬架系统模型，其中同时考虑了不确定参数、未知摩擦力、非线性弹簧和阻尼器以及性能要求。为了处理非线性特性，提出了一种反步控制策略。同时，提出了一种自适应控制策略来处理不确定参数和未知摩擦力。在云辅助车辆悬架系统框架中，自适应反步控制器基于云存储的信息（例如道路信息、车辆悬架信息和参考轨迹）在远程云中更新。最后，提供了具有7自由度模型的整车仿真结果，证明了所提出的控制方案的有效性，并且表明，与被动车辆悬架系统相比，所提出的控制器可以将性能提高80％以上。