Cluster synchronization of stochastic two-layer networks with infinite distributed delays via delayed pinning impulsive control

IF 3.9 4区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS International Journal of Adaptive Control and Signal Processing Pub Date : 2024-03-15 DOI:10.1002/acs.3795

Chuan Zhang, Junchao Wei, Fei Wang, Yi Liang

引用次数: 0

Abstract

The cluster synchronization problem of stochastic two-layer networks with infinite distributed delays is concerned. Firstly, we study the cluster synchronization of the first layer (leader-layer) network with the average state of each cluster of sets as synchronization target. Secondly, we design a delayed pinning impulsive controller to synchronize the second layer (follower-layer) network to the first layer network in a mean square cluster sense. Based on stochastic impulsive analysis and Lyapunov stability theory, some sufficient conditions for cluster synchronization are obtained. Finally, the effectiveness of the theoretical results is verified through numerical simulations.

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通过延迟针刺脉冲控制实现具有无限分布延迟的随机双层网络的簇同步

摘要本研究关注具有无限分布延迟的随机双层网络的簇同步问题。首先，我们研究了第一层（领导层）网络的集群同步问题，以每个集群的平均状态为同步目标。其次，我们设计了一种延迟针刺脉冲控制器，使第二层（跟随层）网络在均方集群意义上与第一层网络同步。基于随机脉冲分析和 Lyapunov 稳定性理论，我们得到了簇同步的一些充分条件。最后，通过数值模拟验证了理论结果的有效性。

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来源期刊

International Journal of Adaptive Control and Signal Processing 工程技术-工程：电子与电气

CiteScore

5.30

自引率

16.10%

发文量

163

审稿时长

5 months

期刊介绍： The International Journal of Adaptive Control and Signal Processing is concerned with the design, synthesis and application of estimators or controllers where adaptive features are needed to cope with uncertainties.Papers on signal processing should also have some relevance to adaptive systems. The journal focus is on model based control design approaches rather than heuristic or rule based control design methods. All papers will be expected to include significant novel material. Both the theory and application of adaptive systems and system identification are areas of interest. Papers on applications can include problems in the implementation of algorithms for real time signal processing and control. The stability, convergence, robustness and numerical aspects of adaptive algorithms are also suitable topics. The related subjects of controller tuning, filtering, networks and switching theory are also of interest. Principal areas to be addressed include: Auto-Tuning, Self-Tuning and Model Reference Adaptive Controllers Nonlinear, Robust and Intelligent Adaptive Controllers Linear and Nonlinear Multivariable System Identification and Estimation Identification of Linear Parameter Varying, Distributed and Hybrid Systems Multiple Model Adaptive Control Adaptive Signal processing Theory and Algorithms Adaptation in Multi-Agent Systems Condition Monitoring Systems Fault Detection and Isolation Methods Fault Detection and Isolation Methods Fault-Tolerant Control (system supervision and diagnosis) Learning Systems and Adaptive Modelling Real Time Algorithms for Adaptive Signal Processing and Control Adaptive Signal Processing and Control Applications Adaptive Cloud Architectures and Networking Adaptive Mechanisms for Internet of Things Adaptive Sliding Mode Control.

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