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Technical Brief

Distributed Event-Triggered Quantizer in Multi-Agent Systems

[+] Author and Article Information
Huaqiang Zhang

Professor
School of Information and Electrical Engineering,
Harbin Institute of Technology at WeiHai,
WeiHai 264209, ShanDong, China
e-mail: zhq@hit.edu.cn

Yu Ren

School of Astronautics,
Harbin Institute of Technology,
Harbin 150001, HeiLongjiang, China
e-mail: 001ren.yu@gmail.com

Xinsheng Wang

Associate Professor
School of Information and Electrical Engineering,
Harbin Institute of Technology at WeiHai,
WeiHai 264209, ShanDong, China
e-mail: wangxswh@126.com

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received July 1, 2013; final manuscript received February 3, 2014; published online April 28, 2014. Assoc. Editor: Gregory Shaver.

J. Dyn. Sys., Meas., Control 136(4), 044504 (Apr 28, 2014) (5 pages) Paper No: DS-13-1257; doi: 10.1115/1.4026875 History: Received July 01, 2013; Revised February 03, 2014

This paper investigates a kind of consensus problem in multi-agent systems, revises an existing control input for consensus by dynamic quantizers, and also gives a visible distributed event-triggered rule to update the parameters for dynamic quantizers. In other words, distributed event-triggered dynamic quantizers are firstly proposed and employed when designing a consensus strategy for multi-agent systems by this paper. Meanwhile, the overall steps of the control strategy are included. The numerical results come to agreement with the theoretical analysis, and shows that the proposed strategy can get faster convergence speed in comparison with an existing one.

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References

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Figures

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Fig. 1

Example for systems described by graph theory

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Fig. 2

Topology of the considered system

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Fig. 3

Four agents of multi-agent system (3) under Eqs. (9) and (15) converge close to their initial average rapidly.

Grahic Jump Location
Fig. 4

Four agents of multi-agent system (3) under the actuation of centralized approach presents in Ref. [8] converge to their initial average.

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