UAV Robust Strategy Control Based on MAS

Abstract

A novel multiagent system (MAS) has been proposed to integrate individual UAV (unmanned aerial vehicle) to form a UAV team which can accomplish complex missions with better efficiency and effect. The MAS based UAV team control is more able to conquer dynamic situations and enhance the performance of any single UAV. In this paper, the MAS proposed and established combines the reacting and thinking abilities to be an initiative and autonomous hybrid system which can solve missions involving coordinated flight and cooperative operation. The MAS uses BDI model to support its logical perception and to classify the different missions; then the missions will be allocated by utilizing auction mechanism after analyzing dynamic parameters. Prim potential algorithm, particle swarm algorithm, and reallocation mechanism are proposed to realize the rational decomposing and optimal allocation in order to reach the maximum profit. After simulation, the MAS has been proved to be able to promote the success ratio and raise the robustness, while realizing feasibility of coordinated flight and optimality of cooperative mission.