Centralized/decentralized event-triggered pinning synchronization of stochastic coupled networks with noise and incomplete transitional rate

This paper studies the synchronous problem of Markovian switching complex networks associated with partly unknown transitional rates, stochastic noise, and randomly coupling strength. In order to achieve the synchronization for these array networks, event-triggered pinning control is established and...

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Bibliographic Details
Published inNeural networks Vol. 121; pp. 10 - 20
Main Authors Dong, Hailing, Zhou, Jiamu, Xiao, Mingqing
Format Journal Article
LanguageEnglish
Published United States Elsevier Ltd 01.01.2020
Subjects
Event-triggered control
Incomplete transitional rates
Markov Chains
Markovian switching
Neural Networks, Computer
Stochastic noise
Stochastic Processes
Synchronization
Stochastic noise
Synchronization
Event-triggered control
Incomplete transitional rates
Markovian switching
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Summary:This paper studies the synchronous problem of Markovian switching complex networks associated with partly unknown transitional rates, stochastic noise, and randomly coupling strength. In order to achieve the synchronization for these array networks, event-triggered pinning control is established and developed, in which the pinning node undergoes a self-adapted switch, governed by a Markov chain. Two types of event-triggered sampling controls, centralized and decentralized event-triggered sampling, respectively, are established. Sufficient conditions for synchronization are developed by constructing a desirable stochastic Lyapunov functional as well as by employing the properties of Markov chain and Itoˆ integration. Numerical simulations are provided to demonstrate the effectiveness of the proposed approach.
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ISSN:0893-6080
1879-2782
DOI:10.1016/j.neunet.2019.09.003