This paper studies the steering and braking coordination control in path tracking problems of intelligent commercial vehicles (ICVs). A gain-scheduled LPV/$H_{\infty }$ strategy for ICVs is proposed to improve tracking performance, driving stability and robustness of controller. While establishing lateral-yaw-roll dynamics, a steering and braking coordination control strategy based on scheduling parameters is designed to enhance tracking accuracy and yaw-roll stability under different driving conditions. The robust performance has been guaranteed in the $H_{\infty }$ robust controller by considering the parameter uncertainties in lateral-yaw-roll dynamic model, unmodeled subsystem as well as ground mechanics and aerodynamics disturbance comprehensively. Also, the dynamic characteristics of time-varying parameters and determination of robust boundary is addressed through a LPV polyhedral structure and a novel Gaussian Process Regression (GPR) model respectively, which reduces the conservativeness of $H_{\infty }$ robust controller. Sufficient conditions for closed-loop stability under the diverse disturbances are provided by the Lyapunov method analytically, which ensures the feasibility of system. The results of simulations on MATLAB-Trucksim platform demonstrate that the proposed controller can significantly enhance tracking accuracy, driving stability, and robustness, which guarantees the feasibility and capability of driving in diverse scenarios.


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    Title :

    Gain-Scheduled ${LPV/H_{\infty }}$ Strategy for Steering and Braking Coordination of Intelligent Commercial Vehicle Lateral Automation


    Contributors:
    Sun, Yingbo (author) / Song, Jiarui (author) / He, Haohui (author) / Xu, Tao (author) / Ji, Xuewu (author)

    Published in:

    Publication date :

    2024-02-01


    Size :

    9070480 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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