This study addresses the path-tracking control issue of autonomous vehicles (AVs) when the GPS measurement is temporarily unavailable. In such a case, the vehicle states, location or the curvature of the reference path might be unobtainable, while the camera can be potentially used to detect the path-tracking states. To this end, this paper proposes a fuzzy-observer-based composite nonlinear feedback (CNF) controller with a Takagi-Sugeno (T-S) vehicle lateral dynamic model to guarantee the normal path-tracking maneuver and improve the transient performance. A parallel distributed compensation (PDC)-based CNF control method is developed to realize the control objective with the T-S vehicle model considering the transient performance and actuator saturation. The closed-loop stability and ${H} _{ \boldsymbol {\infty }}$ index performance integrating the tracking and estimation errors have been proved with a Lyapunov approach. The observer-based controller design has been implemented based on the formulation of the linear matrix inequalities (LMIs). High-fidelity simulations using CarSim-Matlab/Simulink have demonstrated the validity of the proposed approach in terms of enhancing the tracking performance under the input saturation and disturbances in GPS-denied environments.


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    Title :

    Fuzzy Observer-Based Transitional Path-Tracking Control for Autonomous Vehicles


    Contributors:
    Hu, Chuan (author) / Chen, Yimin (author) / Wang, Junmin (author)


    Publication date :

    2021-05-01


    Size :

    2900942 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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