Air traffic management aims to mitigate congestion in air traffic networks mainly caused by capacity constraints of air centers. In this paper, an air traffic network is effectively modeled as a compartmental system, and a model predictive control (MPC) approach with a steady state-input constraint is proposed to mitigate traffic congestion and achieve the departure demand as best as possible. An event-triggered scheme is designed to trigger the solution of the MPC optimization problem when necessary, leading to reduced computational and communication burden. Recursive feasibility of the proposed approach and asymptotic evolution of the system to a steady point are analyzed. The effectiveness of the proposed approach is demonstrated by a five-inflow and three-outflow air traffic network with ten air centers.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Event-Triggered Model Predictive Control for Compartmental Systems with Application to Congestion Control of Air Traffic Networks


    Beteiligte:
    Deng, Li (Autor:in) / Shu, Zhan (Autor:in) / Chen, Tongwen (Autor:in)


    Erscheinungsdatum :

    16.08.2023


    Format / Umfang :

    1035936 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Distributed Event-Triggered Model Predictive Control for Urban Traffic Lights

    Wu, Na / Li, Dewei / Xi, Yugeng et al. | IEEE | 2021



    Robust model predictive ship heading control with event-triggered strategy

    Li, Tailong / Liu, Chenguang / Hou, Guojiao et al. | IEEE | 2023


    Distributed Event-Triggered Model Predictive Control for Spacecraft Swarm

    Sun, Zhaobo / Wu, Baolin / Chen, Junyu | IEEE | 2025