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.


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    Title :

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


    Contributors:

    Published in:

    Publication date :

    2016-02-01




    Type of media :

    Conference paper , Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English