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Optimal distributed fuzzy control strategy for aircraft routing and traffic flow management

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Route planning methods are usually utilized to find the optimum track for an aircraft from the starting to the ending point. For route planning the objective is to satisfy a set of restrict conditions in a certain planning space. In this paper we present a state space linear model of aircraft rout planning and try to generalize the route planning dynamics to node-based data networks. In our presented model the topology is represented by a directed graph, and the Jump Markov model is also proposed for probability change in traffic network topology. Based on the proposed model, we then propose a decentralized fuzzy approach for optimizing the route assignment in a trajectory based air traffic Management environment. Through using fuzzy decision rules in the proposed H-GO controller strategy, we then improve the network performance criteria and avoid traffic in the network. We have shown that the proposed method results in reducing the airspace congestion through efficient route assignment.