Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
404104 | Neural Networks | 2015 | 10 Pages |
This paper presents a new framework for synchronization of complex network by introducing a mechanism of event-triggering distributed sampling information. A kind of event which avoids continuous communication between neighboring nodes is designed to drive the controller update of each node. The advantage of the event-triggering strategy is the significant decrease of the number of controller updates for synchronization task of complex networks involving embedded microprocessors with limited on-board resources. To describe the system’s ability reaching synchronization, a concept about generalized algebraic connectivity is introduced for strongly connected networks and then extended to the strongly connected components of the directed network containing a directed spanning tree. Two sufficient conditions are presented to reveal the underlying relationships of corresponding parameters to reach global synchronization based on algebraic graph, matrix theory and Lyapunov control method. A positive lower bound for inter-event times is derived to guarantee the absence of Zeno behavior. Finally, a numerical simulation example is provided to demonstrate the theoretical results.