This work is the development of a Model Predictive Controller (MPC) for the integrated control of lateral and longitudinal dynamics of a high-performance autonomous car, which follows a given trajectory on a racetrack. The MPC model is based on an Affine-Force-Input single-track nonlinear bicycle model that accounts for actuation dynamics and delays. The MPC problem is formulated as a quadratic problem, enabling efficient real-time solution with a specific quadratic programming (QP) solver. The controller is implemented in and tested in a real-time hardware-in-the-loop (HIL) simulator, showing excellent tracking performance up to 280 km/h.


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    Trajectory Tracking for High-Performance Autonomous Vehicles with Real-Time Model Predictive Control


    Weitere Titelangaben:

    Lect.Notes Mechanical Engineering


    Beteiligte:
    Mastinu, Giampiero (Herausgeber:in) / Braghin, Francesco (Herausgeber:in) / Cheli, Federico (Herausgeber:in) / Corno, Matteo (Herausgeber:in) / Savaresi, Sergio M. (Herausgeber:in) / Pierini, Matteo (Autor:in) / Fusco, Paolo (Autor:in) / Senofieni, Rodrigo (Autor:in) / Corno, Matteo (Autor:in) / Panzani, Giulio (Autor:in)

    Kongress:

    Advanced Vehicle Control Symposium ; 2024 ; Milan, Italy September 01, 2024 - September 05, 2024



    Erscheinungsdatum :

    04.10.2024


    Format / Umfang :

    7 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch