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多无人机编队分组决策与一致性 被引量:9

Grouping of Multi-UAV Formation and the Consistency Protocol
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摘要 针对现阶段分组一致性协议应用的局限性,提出了模糊C-均值聚类算法和考虑子编队之间信息交互的分组一致性控制协议。首先,构建了包含多无人机编队作战关键因素的无人机向量,基于模糊C-均值聚类算法实现了贴合实战需求的编队拆分分组。其次,针对现有分组一致性算法的局限性,提出了一种考虑子编队之间信息交互的分组一致性控制协议,并利用稳定性理论和矩阵论知识推导了相应判据准则。仿真结果表明,所设计的编队分组决策方法和一致性协议可有效实现编队拆分分组和子编队状态的分组一致性,仿真实验验证了判据准则的正确性。 Considering the application limitations of the current grouping consistency protocol, we proposed a fuzzy C-mean clustering algorithm and a new kind of grouping-consistency algorithm based on the information interaction between the groups. Firstly, the UAV vector composed of multiple combat factors is established, and separating/grouping of UAV formation is implemented based on the fuzzy C-mean clustering algorithm. Then, to overcome the deficiency of existing grouping-consistency algorithms, a new kind of grouping-consistency protocol considering the intormation interaction between groups is presented, and the corresponding crilerion is proved based on the theory of stability and nmtrix. The simulation result proved the correctness of the criterion and indicated that the proposed grouping method and consistency protocol can effeclively implement separating/grouping of the UAV formation and guarantee the grouping consistency.
出处 《电光与控制》 北大核心 2017年第10期12-16,共5页 Electronics Optics & Control
基金 航空科学基金(20155196022) 国家自然科学基金(61601505 71501184) 陕西省自然科学基金(2016JQ6050)
关键词 多无人机编队 队形拆分 分组一致性 模糊C-均值聚类 multi-UAV formation formation separation grouping consensus fuzzy C-mean clustering algorithm
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