Adaptive fuzzy funnel control of nonlinear multi-agent systems via dual-channel event-triggered strategy

IF 8.1 1区计算机科学 0 COMPUTER SCIENCE, INFORMATION SYSTEMS

Information Sciences Pub Date : 2025-03-26 DOI:10.1016/j.ins.2025.122129

Xiaoyang Liu , Minghao Hui , Lu Fan , Wenwu Yu , Jinde Cao

引用次数: 0

Abstract

This paper focuses on the constraint control problem of nonlinear multi-agent systems (MASs). An adjustable funnel control is proposed by designing a new transformation variable, which ensures the consensus errors converge within the funnel. By utilizing adaptive fuzzy logic systems, the unknown dynamics of agents are approximated. A novel dual-channel event-triggered strategy is designed by employing the concept of two channels, to save the communication resources and controller resources at the same time. Meanwhile, the Zeno behavior is avoided as well. Two simulation results demonstrate the effectiveness of the proposed control approach.

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本文主要研究非线性多代理系统（MAS）的约束控制问题。通过设计一个新的变换变量，提出了一种可调节的漏斗控制，确保共识误差在漏斗内收敛。通过利用自适应模糊逻辑系统，对代理的未知动态进行了近似。利用双通道的概念设计了一种新颖的双通道事件触发策略，以同时节省通信资源和控制器资源。同时，还避免了 Zeno 行为。两个仿真结果证明了所提控制方法的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Information Sciences 工程技术-计算机：信息系统

CiteScore

14.00

自引率

17.30%

发文量

1322

审稿时长

10.4 months

期刊介绍： Informatics and Computer Science Intelligent Systems Applications is an esteemed international journal that focuses on publishing original and creative research findings in the field of information sciences. We also feature a limited number of timely tutorial and surveying contributions. Our journal aims to cater to a diverse audience, including researchers, developers, managers, strategic planners, graduate students, and anyone interested in staying up-to-date with cutting-edge research in information science, knowledge engineering, and intelligent systems. While readers are expected to share a common interest in information science, they come from varying backgrounds such as engineering, mathematics, statistics, physics, computer science, cell biology, molecular biology, management science, cognitive science, neurobiology, behavioral sciences, and biochemistry.