A novel method of topology identification for general complex dynamical networks with incomplete measurements

Xinwei Wang (), Guo-Ping Jiang and Xu Wu ()
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Xinwei Wang: College of Automation, Nanjing University of Posts and Telecommunications, No. 9, Wenyuan Road, Nanjing, Jiangsu 210023, P. R. China
Guo-Ping Jiang: College of Automation, Nanjing University of Posts and Telecommunications, No. 9, Wenyuan Road, Nanjing, Jiangsu 210023, P. R. China
Xu Wu: College of Automation, Nanjing University of Posts and Telecommunications, No. 9, Wenyuan Road, Nanjing, Jiangsu 210023, P. R. China

International Journal of Modern Physics C (IJMPC), 2018, vol. 29, issue 05, 1-14

Abstract: 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.

Keywords: Topology identification; complex dynamical network; incomplete measurements (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1142/S0129183118400016

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