Decentralized topology identification of complex networks with sensor random delays and disturbances

A topology identification scheme based on decentralized control architecture is proposed for a complex network with sensor random delays and disturbances. Each node uses the information transmitted from its neighboring nodes to establish the adaptive observers which can correctly identify the links between it and its neighboring nodes. The information is not needed to be exchange between the nodes and its neighboring ones in the adaptive observer so that the disadvantages induced by the communications of the observer are avoided including time delays and disturbances. The proposed scheme can be extended to the other complex networks such as time-delayed network and nominal network. Finally, some numerical simulations are given to demonstrate the effectiveness of the proposed topology identification scheme.

[1]  Marcelo Godoy Simões,et al.  Power quality achievement using grid connected converter of wind turbine system , 2015, 2015 IEEE Industry Applications Society Annual Meeting.

[2]  Lixiang Li,et al.  Finite-time topology identification and stochastic synchronization of complex network with multiple time delays , 2017, Neurocomputing.

[3]  Ahmed Al-Durra,et al.  Designing smart inverter with unified controller and smooth transition between grid-connected and islanding modes for microgrid application , 2015, 2015 IEEE Industry Applications Society Annual Meeting.

[4]  Donatello Materassi,et al.  Topological identification in networks of dynamical systems , 2008, 2008 47th IEEE Conference on Decision and Control.

[5]  Song Zheng,et al.  Topology Identification of Weighted Complex Dynamical Networks with Non-Delayed and Time-Varying Delayed Coupling , 2010 .

[6]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[7]  Sharon I. Greenblum,et al.  Metagenomic systems biology of the human gut microbiome reveals topological shifts associated with obesity and inflammatory bowel disease , 2011, Proceedings of the National Academy of Sciences.

[8]  Yuhua Xu,et al.  Topology identification of the modified complex dynamical network with non-delayed and delayed coupling , 2012 .

[9]  Junan Lu,et al.  Structure identification of uncertain general complex dynamical networks with time delay , 2009, Autom..

[10]  Fan Chunxia,et al.  Topology identification for a class of complex dynamical networks using output variables , 2012 .

[11]  Wei Xing Zheng,et al.  Inferring topologies of complex networks with hidden variables. , 2012, Physical review. E, Statistical, nonlinear, and soft matter physics.

[12]  Nathalie Corson,et al.  Sinusoidal disturbance induced topology identification of Hindmarsh-Rose neural networks , 2016, Science China Information Sciences.

[13]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.

[14]  Mehran Mesbahi,et al.  Network identification via node knock-out , 2010, 49th IEEE Conference on Decision and Control (CDC).

[15]  Min Zou,et al.  A new dynamic Bayesian network (DBN) approach for identifying gene regulatory networks from time course microarray data , 2005, Bioinform..

[16]  Giorgio Battistelli,et al.  Detecting topology variations in networks of linear systems with static coupling , 2016, 2016 IEEE 55th Conference on Decision and Control (CDC).

[17]  Xiaoqun Wu,et al.  Topology identification of two-layer unidirectional complex dynamical networks based on auxiliary system approach , 2016, 2016 Chinese Control and Decision Conference (CCDC).

[18]  Zhidong Teng,et al.  Parameter identification based on finite-time synchronization for Cohen–Grossberg neural networks with time-varying delays , 2015 .

[19]  Victor M. Preciado,et al.  Robust topology identification and control of LTI networks , 2014, 2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP).

[20]  Liang Chen,et al.  Synchronization: An Obstacle to Identification of Network Topology , 2009, IEEE Transactions on Circuits and Systems II: Express Briefs.

[21]  E. Kunkel Systems biology in drug discovery , 2004, Nature Biotechnology.

[22]  Mao-Yin Chen,et al.  Synchronization in Complex Dynamical Networks With Random Sensor Delay , 2010, IEEE Transactions on Circuits and Systems II: Express Briefs.

[23]  Haipeng Peng,et al.  Impulsive control for synchronization and parameters identification of uncertain multi-links complex network , 2016 .

[24]  H. Kitano Systems Biology: A Brief Overview , 2002, Science.

[25]  Junan Lu,et al.  Identifying Topologies of Complex Dynamical Networks With Stochastic Perturbations , 2016, IEEE Transactions on Control of Network Systems.

[26]  Di Ning,et al.  Reconstruction of complex networks with delays and noise perturbation based on generalized outer synchronization , 2016 .