Neural-network-based fully distributed formation control for nonlinear multi-agent systems with event-triggered communication

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外文摘要：This paper investigates the consensus-based formation control problem for multi-agent systems with unknown nonlinear dynam-ics.To achieve the desired formation,we propose two formation controllers to achieve the desired formation,one based on system states and the other on system outputs.The proposed controllers utilize adaptive gains to avoid global information and neural networks to estimate and compensate for nonlinearities.The proposed event-triggered schemes avoid continuous communica-tion among agents and exclude the Zeno behavior.Stability analysis reveals that formation errors are bounded,and numerical simulations are used to validate the effectiveness of the proposed approaches.

外文关键词：

formation controlneural networkadaptive controlevent-triggered communicationmulti-agent systems

作者：

ZHU GuoLiang、LIU KeXin、GU HaiBo、Lü JinHu

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作者单位：

School of Automation Science and Electrical Engineering,Beihang University Beijing 100191,China

Zhongguancun Laboratory,Beijing 100094,China

基金：

National Key R&D Program of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaFundamental Research Funds for Central Universities of China

项目编号：

2022YFB3305600621030156214160492067204YWF-23-03-QB-019

出版年：

2024

DOI：

10.1007/s11431-022-2410-1

中国科学:技术科学(英文版)

中国科学院

中国科学:技术科学(英文版)

CSTPCDEI

影响因子：1.056

ISSN：1674-7321

年,卷(期)：2024.67(1)

参考文献量38