As the level of vehicle intelligence increases, the amount of communication data is also constantly increasing. At the same time, there is parameter uncertainty and unknown disturbances in the vehicle system modeling poses challenges to the precise control of vehicle states. To address these challenges, an event-triggered adaptive fuzzy control is presented. The fuzzy logic system (FLS) approximates the boundary of uncertain parameters and nonlinearity in the control system, which ensures control accuracy and robustness of the system. Additionally, to reduce the communication burden of the vehicle, an event-triggering strategy with relative threshold values is designed. This controller ensures that the control error converges to a neighborhood near the zero point while avoiding the Zeno behavior. The experimental results indicate that the control strategy ensures the control accuracy and reduces the communication burden. This approach provides an effective solution for designing lateral motion controllers for autonomous vehicles.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Event-Triggered Adaptive Fuzzy Approach-Based Lateral Motion Control for Autonomous Vehicles


    Contributors:

    Published in:

    Publication date :

    2024-01-01


    Size :

    4478516 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Adaptive Backstepping Fuzzy Lateral Motion Control Approach for Autonomous Vehicles

    Zhang, Lipeng / Zhang, Junda / Liu, Shuaishuai et al. | IEEE | 2024




    Lateral control of autonomous vehicles based on fuzzy logic

    Wang, Xinyu / Fu, Mengyin / Ma, Hongbin et al. | Tema Archive | 2015


    REAL TIME EVENT TRIGGERED FEEDBACK FOR AUTONOMOUS VEHICLES

    VAN DER LOWE ILMO / WRIGHT CLEMENT / KAMAT PRIYA | European Patent Office | 2023

    Free access