In order to accomplish the objective of trajectory tracking control for a smart vehicle, a controller utilizing model predictive control (MPC) is designed. To this end, a nonlinear dynamic model of vehicle dynamics with tire slip rate is first established, and then linearized and discretized. Next, the vehicle's front wheel deflection angle is used as the controller input, and the objective of the control is to reduce the error between the actual track and the target trajectory while taking into account the vehicle's actual structure, various constraints under actual driving conditions, adding soft constraints to the system output, and optimizing trajectory tracking. To verify the efficacy of the aforementioned trajectory tracking controller, a joint simulation system is constructed utilizing the Carsim-Simulink platform. The system carries out the typical trajectory tracking simulation tests at different vehicle speeds. The results of the simulation indicate that the proposed controller exhibits a greater ability to follow the typical trajectory path while controlling intelligent cars, making it a viable option for trajectory tracking control of future smart vehicles.


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    Title :

    Simulation Research on MPC-Based Intelligent Vehicle Trajectory Tracking Control


    Contributors:
    Ling, Li (author) / Yueru, Zhao (author)


    Publication date :

    2023-11-17


    Size :

    664319 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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