Event-triggered synchronization strategy for complex dynamical networks with the Markovian switching topologies

• Published in: Neural networks Vol. 74; pp. 52 - 57
• Main Authors: Wang, Aijuan, Dong, Tao, Liao, Xiaofeng
• Format: Journal Article
• Language: English
• Published: United States Elsevier Ltd 01.02.2016
• Subjects: Algorithms; Asynchronous intermittent communication; Complex networks; Computer Simulation; Discrete-time event detection; Event-triggering; Markov Chains; Markovian switching topologies; Neural Networks (Computer); Synchronization; Time Perception; Asynchronous intermittent communication; Markovian switching topologies; Event-triggering; Synchronization; Complex networks; Discrete-time event detection
• ISSN: 0893-6080; 1879-2782
• DOI: 10.1016/j.neunet.2015.11.002

This paper concerns the synchronization problem of complex networks with the random switching topologies. By modeling the switching of network topologies as a Markov process, a novel event-triggered synchronization strategy is proposed. Unlike the existing strategies, the event detection of this strategy only works at the network topology switching time instant, which can significantly decrease the communication frequency between nodes and save the network resources. Under this strategy, the synchronization problem of complex network is equivalently converted to the stability of a class of Markovian jump systems with a time-varying delay. By using the Lyapunov–Krasovskii functional method and the weak infinitesimal operation, a sufficient condition for the mean square synchronization of the complex networks subject to Markovian switching topologies is established. Finally, a numerical simulation example is provided to demonstrate the theoretical results.