In this paper, a stochastic near-optimal control method is proposed for determining aircraft conflict-resolution trajectories in the presence of uncertainty in real time. The prior work developed a stochastic optimal control method for aircraft conflict resolution based on the polynomial chaos expansion and pseudospectral methods. This stochastic optimal control method is extended to generate conflict-resolution trajectories in real time without actually solving the computationally expensive stochastic optimal control problems. The proposed near-optimal conflict-resolution algorithm is based on a recently developed surrogate modeling technique called polynomial chaos kriging, which is used to construct the surrogate models of the optimal conflict-resolution trajectories from a set of precomputed optimal solutions. The near-optimal conflict-resolution trajectories can be accurately generated in real time from the surrogate models with the information of current conditions (for example, current states). Through illustrative aircraft conflict-resolution examples, the performance and effectiveness of the proposed stochastic near-optimal conflict-resolution algorithm are evaluated and demonstrated.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Near-Optimal Control for Aircraft Conflict Resolution in the Presence of Uncertainty


    Beteiligte:

    Erschienen in:

    Erscheinungsdatum :

    2015-07-24


    Format / Umfang :

    13 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch






    Stochastic optimal control for aircraft conflict resolution under wind uncertainty

    Matsuno, Yoshinori / Tsuchiya, Takeshi / Wei, Jian et al. | Elsevier | 2015



    Decentralized multi-aircraft conflict resolution in the presence of uncertainty

    Lin-quan Fang, / Kai-quan Cai, / Yang Yang, et al. | IEEE | 2015