Exponential synchronization of complex networks via feedback control and periodically intermittent noise

被引：21
作者：
He, Xiuli [1 ]
Zhang, Huiyan [2 ]
机构：
[1] Hohai Univ, Coll Sci, Nanjing 210098, Peoples R China
[2] Chongqing Technol & Business Univ, Natl Res Base Intelligent Mfg Serv, Chongqing 400067, Peoples R China
来源：
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS | 2022年 / 359卷 / 08期
基金：
中国国家自然科学基金;
关键词：
NEURAL-NETWORKS; TIME; STABILITY; SYSTEMS; STABILIZATION;
D O I：
10.1016/j.jfranklin.2022.03.010
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In complex networks, asymptotic properties play an important role in modeling, analysis and design in both aspects of theory and practice. In this paper, our focus is on exponential synchronization for a class of complex networks. Under certain conditions, a feedback control and stochastic periodically intermittent noise are designed to synchronize the networks. Such synchronization scheme needs less control energy due to the usage of the intermittent noise. The threshold of intermittent rate for synchronization scheme is derived. Moreover, the noise states are observed in discrete-time mode, which reduces the complexity and the computation burden for continuous observations. The observation supremum is obtained by solving a transcendental equation. Finally, a simulation example is provided, and the comparison results with some existing methods illustrate the effectiveness and advantages of the proposed new design strategy. (C) 2022 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码：3614 / 3630
页数：17
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