基于模式的半马尔可夫核交换动态网络同步触发协议及其应用

IF 3.4 2区 数学 Q1 MATHEMATICS, APPLIED Applied Mathematics and Computation Pub Date : 2025-06-15 Epub Date: 2025-02-07 DOI:10.1016/j.amc.2025.129336
Mengshen Chen , Derui Ding , Huaicheng Yan , Kun Liang
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引用次数: 0

摘要

本文利用半马尔可夫核方法研究了具有随机切换拓扑的离散动态网络的均方同步问题。为了降低通信频率,提出了一种基于模式的触发协议,使得耦合节点之间的数据只在拓扑切换时刻传输。此外,首先采用基于半马尔可夫核方法的更一般的半马尔可夫链来描述网络拓扑的随机切换过程,使得不同类型的概率密度函数可以在任意拓扑模式下共存。在该触发策略下,形成了一种基于模式的分布式同步协议,解决了半马尔可夫切换的随机性给控制器设计带来的困难。基于Lyapunov函数,避免了已有结果中的一些辅助不等式,进一步得到了保证动态网络均方同步的数值可检验准则。最后,以电力系统为例,验证了该方法的有效性。
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Mode-based triggered protocol for synchronization of switched dynamic networks with semi-Markov kernel and its application
In this paper, the mean square synchronization is investigated for discrete-time dynamic networks with stochastic switching topologies via a semi-Markov kernel approach. A novel mode-based triggered protocol is developed to reduce the communication frequency, where the data between coupled nodes is only transmitted at the topology switching instants. Besides, a more general semi-Markov chain based on the semi-Markov kernel approach is first adopted to describe the stochastic switching process of network topologies, then the different types of probability density functions can coexist in any topological mode. Under the proposed triggering strategy, a mode-based distributed synchronization protocol is formed to deal with the controller design difficulty caused by the randomness of semi-Markov switching. Based on the Lyapunov function, some auxiliary inequalities in existing results are avoided and further the numerically testable criterion is obtained to ensure mean square synchronization of the dynamic networks. Finally, a practical example of power systems is presented to demonstrate the effectiveness of the proposed method.
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来源期刊
CiteScore
7.90
自引率
10.00%
发文量
755
审稿时长
36 days
期刊介绍: Applied Mathematics and Computation addresses work at the interface between applied mathematics, numerical computation, and applications of systems – oriented ideas to the physical, biological, social, and behavioral sciences, and emphasizes papers of a computational nature focusing on new algorithms, their analysis and numerical results. In addition to presenting research papers, Applied Mathematics and Computation publishes review articles and single–topics issues.
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