Topology identification of an uncertain general complex dynamical network

Author(s):  
Hui Liu ◽  
Junan Lu ◽  
Jinhu Lu
2018 ◽  
Vol 29 (05) ◽  
pp. 1840001
Author(s):  
Xinwei Wang ◽  
Guo-Ping Jiang ◽  
Xu Wu

Recovering the topological structure of a general complex dynamical network with the incomplete measurements of transmitted drive states is investigated in this paper. The incomplete measurements, which cannot be ignored, have not been well considered in topology identification issue. Different from previous studies, we propose a novel method which can handle the situation of incomplete measurements well. The proposed method can fix the excessive deviation of the controller caused by the incomplete measurements, and overcome the special restrictions on the node dynamics raised by the previous methods. By means of LaSalle’s invariance principle, mathematical derivation of the mechanism is deduced rigorously to obtain the sufficient criteria in the form of linear matrix inequalities. Numerical simulations with the complex dynamical network composed of chaotic dynamical nodes are given to illustrate the effectiveness of our proposed method.


2013 ◽  
Vol 411-414 ◽  
pp. 2093-2097
Author(s):  
Jiang Ang Zhang ◽  
Yan Dong Chu ◽  
Wen Ju Du

Recently, various papers investigated the topology identification and parameter identification of uncertain general complex dynamical networks. However, in many real complex dynamical network systems, there exists community or hierarchical structure and node delay. Based on LaSalle’s invariance principle, in this letter, an adaptive controlling method is proposed to identify unknown topological structure for general weighted complex dynamical network with community and node delay. Illustrative simulations are provided to verify the correctness and effectiveness of the proposed scheme.


2013 ◽  
Vol 2013 ◽  
pp. 1-8
Author(s):  
Jin Zhou

Synchronization of complex networks has been extensively studied in many fields, where intensive efforts have been devoted to the understanding of its mechanisms. As for discriminating network synchronizability by Master Stability Function method, a dilemma usually encountered is that we have no prior knowledge of the network type that the synchronous region belongs to. In this paper, we investigate a sufficient condition for a general complex dynamical network in the absence of control. A main result is that, when the coupling strength is sufficiently strong, the dynamical network achieves synchronization provided that the symmetric part of the inner-coupling matrix is positive definite. According to our results, synchronous region of the network with positive definite inner-coupling matrix belongs to the unbounded one, and then the eigenvalue of the outer-coupling matrix nearest 0 can be used for judging synchronizability. Even though we cannot gain the necessary and sufficient conditions for synchronizing a network so far, our results constitute a first step toward a better understanding of network synchronization.


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