This paper proposes a Networked Model Predictive Control (NMPC) approach for vehicle racing scenarios with multiple participants. The control algorithm incorporates a trajectory optimization problem for each vehicle, which is solved in a receding horizon way. Sequential Quadratic Programming (SQP) is used for optimization. The individual vehicle controllers are coupled via collision avoidance constraints or a blocking objective term, depending on the race situation, leading to a Networked Control System (NCS). We demonstrate our method in simulations. It produces realistic racing situations, showing overtaking and blocking maneuvers while avoiding collisions. With optimization times in the order of a few milliseconds, real-time applications seem possible.


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    Title :

    Networked Model Predictive Vehicle Race Control


    Contributors:


    Publication date :

    2019-10-01


    Size :

    757295 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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