Connected and autonomous driving technology is a current research hotspot, which can effectively ease transportation congestion and enhance road safety. This paper addresses the control problem of heterogeneous vehicle platoons subject to various disturbances, including but not limited to modeling and measurement disturbances. The problem is approached by a tube-based distributed model predictive control (MPC) algorithm that relies on a unidirectional predecessor-following communication topology. To improve the computational efficiency of the algorithm, the inherently nonlinear MPC problem is formulated as a convex program in the spatial domain by coordination changes and suitably relaxing the nonconvex constraints. Numerical simulation examples are carried out to show the effectiveness and robustness of the proposed control algorithm.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Tube-based Distributed Model Predictive Control for Heterogeneous Vehicle Platoons via Convex Optimization


    Contributors:
    Sun, Hao (author) / Dai, Li (author) / Chen, Boli (author)


    Publication date :

    2022-10-08


    Size :

    732423 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




    Cooperative distributed predictive control for collision‐free vehicle platoons

    Zheng, Huarong / Wu, Jun / Wu, Weimin et al. | Wiley | 2019

    Free access

    Cooperative distributed predictive control for collision-free vehicle platoons

    Zheng, Huarong / Wu, Jun / Wu, Weimin et al. | IET | 2019

    Free access

    String stable model predictive cooperative adaptive cruise control for heterogeneous platoons

    van Nunen, E / Reinders, J.M.F. / Semsar-Kazerooni, Elham et al. | BASE | 2019

    Free access

    String Stable Model Predictive Cooperative Adaptive Cruise Control for Heterogeneous Platoons

    van Nunen, Ellen / Reinders, Joey / Semsar-Kazerooni, Elham et al. | IEEE | 2019