This paper presents a model predictive controller (MPC) structure for solving the path-tracking problem of terrestrial autonomous vehicles. To achieve the desired performance during high-speed driving, the controller architecture considers both the kinematic and the dynamic control in a cascade structure. Our study contains a comparative study between two kinematic linear predictive control strategies: The first strategy is based on the successive linearization concept, and the other strategy combines a local reference frame with an approaching path strategy. Our goal is to search for the strategy that best comprises the performance and hardware-cost criteria. For the dynamic controller, a decentralized predictive controller based on a linearized model of the vehicle is used. Practical experiments obtained using an autonomous ldquoMini-Bajardquo vehicle equipped with an embedded computing system are presented. These results confirm that the proposed MPC structure is the solution that better matches the target criteria.


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    Titel :

    A Predictive Controller for Autonomous Vehicle Path Tracking


    Beteiligte:
    Raffo, G.V. (Autor:in) / Gomes, G.K. (Autor:in) / Normey-Rico, J.E. (Autor:in) / Kelber, C.R. (Autor:in) / Becker, L.B. (Autor:in)


    Erscheinungsdatum :

    01.03.2009


    Format / Umfang :

    848345 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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