DocumentCode :
2727434
Title :
Adaptive synchronization-based approach for real-time identification of coupling delays or node delays in dynamical complex networks
Author :
Xiaoming Wu ; Zhiyong Sun ; Feng Liang ; Changbin Vu
Author_Institution :
Shandong Provincial Key Lab. of Comput. Network, Shandong Comput. Sci. Center, Jinan, China
fYear :
2013
fDate :
12-14 June 2013
Firstpage :
777
Lastpage :
782
Abstract :
The control and synchronization of time-delayed complex networks have gained considerable attention recently. However, in the existing literature there is few result on the delay estimation in complex networks. In this paper, based on the observer concept and the adaptive synchronization strategy, we present a general and systematic method to estimate the unknown time delays in complex networks. Two kinds of delays, the coupling delays and the node delays, are considered. Several criteria are obtained for the real time identification of the unknown network delays. The local stability of the augmented error systems is proved via the Lyapunov-Krasovskii functional approach and the Barbalat´s Lemma. Two typical examples are presented to verify the effectiveness of the proposed approach.
Keywords :
Lyapunov methods; complex networks; delay estimation; observers; stability; synchronisation; time-varying networks; Barbalats lemma; Lyapunov-Krasovskii functional approach; adaptive synchronization-based approach; augmented error systems local stability; controller design; coupling delays; dynamical complex networks; node delays; observer concept; real-time identification; time delay estimation; time-delayed complex networks; unknown network delay identification; Adaptive systems; Complex networks; Couplings; Delay estimation; Observers; Synchronization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control and Automation (ICCA), 2013 10th IEEE International Conference on
Conference_Location :
Hangzhou
ISSN :
1948-3449
Print_ISBN :
978-1-4673-4707-5
Type :
conf
DOI :
10.1109/ICCA.2013.6565048
Filename :
6565048
Link To Document :
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