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Cooperative control of UAV based on Multi-Agent System

机译:基于多Agent系统的无人机协同控制

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A initiative and self-governing hybrid Agent system having fine capabilities of reaction and thinking has been designed to solve the problem of UAV(Unmanned Aerial Vehicle) Coordinated flight and Cooperative mission. UAV coordinated flight is realized by devising the tracking algorithm and Artificial Potential Field method in the system. For the cooperative mission in the system, the BDI model is used to model and classify the mission. Via analyzing the coupled and dynamic properties of the mission, the algorithms of auction and bidding are devised by utilizing auction mechanism improved through Prim Potential Algorithm and Particle Swarm Algorithm to complete the rational decomposing and optimal allocation of the mission then to achieve the maximum of the system profit. After calculating and simulating by the software, this system has been proved owning flexibility and stability and being able to realize the feasibility of coordinated flight and the optimality of cooperative mission, it can save human resources as well as promote the success ratio and efficiency of accomplishing the mission, at the same time, provide a great theoretical basis for the future realization of the actual UAV battle synergy.
机译:为了解决无人机协同飞行与协同任务的问题,设计了一种具有良好反应和思考能力的主动,自治的混合智能体系统。通过在系统中设计跟踪算法和人工势场方法,实现了无人机协同飞行。对于系统中的协作任务,BDI模型用于对任务进行建模和分类。通过分析任务的耦合和动态特性,利用原始势能算法和粒子群算法改进的拍卖机制,设计了拍卖和出价算法,完成了任务的合理分解和最优分配,从而实现了任务的最大化。系统利润。经过软件计算和仿真,证明该系统具有灵活性和稳定性,能够实现协同飞行的可行性和协同任务的最优性,可以节省人力资源,提高成功率和完成效率。同时,该任务为将来实现实际的无人机战斗协同作用提供了重要的理论基础。

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