具有切换拓扑的冲动型多代理系统中的领导者选择

IF 9.4 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS IEEE Transactions on Cybernetics Pub Date : 2024-09-25 DOI:10.1109/TCYB.2024.3457783
Kaile Chen;Mengqi Xue;Jiahao Huang;Wen Yang;Wei Xing Zheng;Yang Tang
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引用次数: 0

摘要

在领导者-追随者多代理系统(MASs)中,寻求一种有效的方案来选择一组代理作为领导者,对于实现预期的合作绩效非常重要。本文研究了具有切换拓扑的冲动型一般线性 MAS 的最小领导者选择问题。本研究的重点是选择一组直接接收参考信号信息的代理作为领导者,同时在保证一致跟踪性能的前提下尽量减少领导者的数量。首先,采用平均停留时间技术和时间比率约束,得出共识跟踪的明确标准,作为选择领导者的前期准备。其次,应用子模态优化框架,根据推导出的标准建立领导者选择指标。第三,运用贪婪规则,根据建立的指标提出了一个高效的领导者选择方案。该方案由两个多项式时间算法组成,所选领导者集的返回值在最优值的对数范围内。最后,通过一个示例验证了所开发的领导者选择方案的有效性。
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Leader Selection in Impulsive Multiagent Systems With Switching Topologies
In leader-follower multiagent systems (MASs), seeking an efficient scheme to select a set of agents as leaders is important for realizing the expected cooperative performance. In this article, the problem of minimal leader selection is investigated for impulsive general linear MASs with switching topologies. This study focuses on selecting a set of agents as leaders that receive information from a reference signal directly, while minimizing the number of leaders, subject to consensus tracking performance. First, adopting the average dwell time technique and a time-ratio constraint, an explicit criterion for consensus tracking is derived as prepreparation for leader selection. Second, applying the submodular optimization framework, leader selection metrics are established based on the derived criterion. Third, employing the greedy rule, an efficient leader selection scheme is presented according to the established metrics. The scheme comprises two polynomial-time algorithms that return selected leader sets within a logarithmic bound of the optimum. Finally, the effectiveness of the developed leader selection scheme is verified using an illustrative example.
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来源期刊
IEEE Transactions on Cybernetics
IEEE Transactions on Cybernetics COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, CYBERNETICS
CiteScore
25.40
自引率
11.00%
发文量
1869
期刊介绍: The scope of the IEEE Transactions on Cybernetics includes computational approaches to the field of cybernetics. Specifically, the transactions welcomes papers on communication and control across machines or machine, human, and organizations. The scope includes such areas as computational intelligence, computer vision, neural networks, genetic algorithms, machine learning, fuzzy systems, cognitive systems, decision making, and robotics, to the extent that they contribute to the theme of cybernetics or demonstrate an application of cybernetics principles.
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