期刊
NEUROCOMPUTING
卷 157, 期 -, 页码 199-207出版社
ELSEVIER
DOI: 10.1016/j.neucom.2015.01.018
关键词
Event-triggered synchronization; Complex networks; Pinning control; Combinational measurement; Convergence rate
资金
- National Natural Science Foundation of China [61170249, 61273021]
- Natural Science Foundation Project of CQ [cstc2013jjB40008]
- Research Fund of Preferential Development Domain for the Doctoral Program of Ministry of Education of China [201101911130005]
- Program for Changjiang Scholars
- fundamental research funds for the central universities [XDJK2014D029]
- NPRP Grant from the Qatar National Research Fund (a member of Qatar Foundation) [4-1162-1-181]
In this paper, we consider the pinning exponential synchronization of complex networks via event-triggered communication. By using the combinational measurements, two classes of event triggers are designed, one depends on continuous communications between the agents, the other avoids the continuous communications. The controller updates when triggering function reaches certain threshold. For such classes of two event triggers, the exponential synchronization as well as the convergence rate of the controlled complex networks are studied, respectively, by employing the M-matrix theory, algebraic graph theory and the Lyapunov method. Two simulation examples are provided to illustrate the effectiveness of the proposed two classes of event triggering strategies. It is noteworthy that the event trigger with combinational measurements avoids decoupling the actual state of the nodes, which is more effective than the error-based event trigger. (C) 2015 Elsevier B.V. All rights reserved.
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