Delay-induced consensus of fractional-order complex networks via intermittent sampled position control

IF 8.1 1区 计算机科学 0 COMPUTER SCIENCE, INFORMATION SYSTEMS
Yanyan Ye , Lei Ouyang , Zhixia Ding , Yao Zhao
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引用次数: 0

Abstract

This paper investigates the consensus problem of fractional-order complex networks via intermittent sampled position control. A delay-induced consensus protocol with intermittent sampled position for the fractional-order system is proposed, where only the current and delayed sampled positions are used. Meanwhile, the controllers operate only for a period of time in each sampling interval, which decrease the working time and update rates of controllers. Successively, by discussing four situations involving delay, sampling period, and communication width, necessary and sufficient consensus criteria are presented. It is interesting to find the delay has a positive impact on consensus of fractional-order complex networks, since consensus cannot be achieved without delay under the proposed protocol. Finally, simulation examples are presented to illustrate the theoretical analysis.
通过间歇采样位置控制实现分数阶复杂网络的延迟诱导共识
本文通过间歇采样位置控制研究了分数阶复杂网络的共识问题。针对分数阶系统提出了一种间歇采样位置的延迟诱导共识协议,其中只使用当前和延迟采样位置。同时,控制器在每个采样间隔内只运行一段时间,从而减少了控制器的工作时间和更新率。随后,通过讨论涉及延迟、采样周期和通信宽度的四种情况,提出了必要和充分的共识标准。值得注意的是,延迟对分数阶复杂网络的共识有积极影响,因为在所提出的协议下,没有延迟就无法达成共识。最后,还列举了一些仿真实例来说明理论分析。
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
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.
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