Aiming at the stability control problem of the non-linear dynamic characteristics of vehicles, this paper proposes a kernel based dual heuristic programming(KD HP) intelligent vehicle stability control strategy, and establishes a two-degree-of-freedom vehicle model considering tire nonlinearity. The method of approximate linear correlation analysis(ALD) is used to sparse the sampled data, and a kernel dictionary is established. Carsim/Simulink joint simulation shows that under the double lane changing condition and the double lane emer-gency lane changing condition, the KDHP controller has better tracking accuracy than the dual heuristic programming(DHP) controller, and can better adapt to the nonlinear system.


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    Titel :

    Kernel-based Approximate Dynamic Programming for Autonomous Vehicle Stability Control


    Beteiligte:
    Guo, Hongyan (Autor:in) / Tan, Zhongqiu (Autor:in) / Liu, Jun (Autor:in) / Guo, Jingzheng (Autor:in)


    Erscheinungsdatum :

    2022-10-08


    Format / Umfang :

    2913528 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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