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Tracking Control for the Connection Relationships of Discrete-time Complex Dynamical Network Associated with the Controlled Nodes

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  • Control Theory and Applications
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Abstract

In this paper, a general discrete-time complex dynamical network is regarded to be composed of the nodes subsystem and the links subsystem which are mutually coupled. Different from the existing researches on the stabilization and synchronization of nodes group, this paper mainly focuses on the dynamical behavior of connection relationships between the nodes, and the network nodes only play a helping and secondary role in the dynamics of connection relationships. Due to the state of the links subsystem is difficult to be measured accurately in practice appliances, the Riccati difference equation without any control input is employed as the dynamic model of the links subsystem, in which the dynamic coupling term is the first order polynomial about the state of nodes. With the helping of controlled nodes, the tracking problem is discussed for the links subsystem. By using the coupling algebraic relation between the reference tracking targets of the nodes subsystem and the given tracking target of the links subsystem, the tracking control scheme is proposed for the nodes subsystem to force the links subsystem converges asymptotically to the given target. Finally, the simulations are used to show the validity of the method in this paper.

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Author information

Authors and Affiliations

  1. School of Automation, Guangdong University of Technology, Guangzhou, 51006, P. R. China

    Li-zhi Liu & Yin-he Wang

  2. School of Computer Science and Engineering, Chongqing Three Gorges University, Chongqing, 404100, P. R. China

    Zi-lin Gao

Authors
  1. Li-zhi Liu
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Corresponding author

Correspondence to Li-zhi Liu.

Additional information

Recommended by Editor Jessie(Ju H.) Park. This study was funded by the National Science Foundation of China (grant number 61673120), and the Scientific and Technological Research Program of Chongqing Municipal Education Commission (grant number KJ1710244, KJ201801215).

Li-zhi Liu received his B.S. degree in Automation from Panzhihua University, Panzhihua, P. R. China, in 2016. Now, he is currently working toward a Ph.D. degree in control theory and engineering at Guangdong University of Technology. His research interests include analysis and control for nonlinear systems and complex dynamical networks, and artificial neural network.

Yin-he Wang received his M.S. degree in mathematics from Sichuan Normal University, Chengdu, P. R. China, in 1990, and his Ph.D. degree in control theory and engineering from Northeastern University, Shenyang, P. R. China, in 1999. From 2000 to 2002, he was a Post-doctor in Department of Automatic control, Northwestern Polytechnic University, Xi’an, P. R. China. From 2005 to 2006, he was a visiting scholar at Department of Electrical Engineering, Lakehead University, Canada. He is currently a Professor with the School of Automation, Guangdong University of Technology, Guangzhou, China. His research interests include fuzzy adaptive robust control, analysis for nonlinear systems and complex dynamical networks.

Zi-lin Gao received his M.S. degree in control theory and engineering from Guangdong University of Technology, Guangzhou, P. R. China, in 2013. Then he is a lecturer with the School of Computer Science and Engineering, Chongqing Three Gorges University, Chongqing, P. R. China. Now, he is currently working toward a Ph.D. degree in control theory and engineering at Guangdong University of Technology. His research interests include analysis and control for nonlinear systems and complex dynamical networks.

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Liu, Lz., Wang, Yh. & Gao, Zl. Tracking Control for the Connection Relationships of Discrete-time Complex Dynamical Network Associated with the Controlled Nodes. Int. J. Control Autom. Syst. 17, 2252–2260 (2019). https://doi.org/10.1007/s12555-018-0928-6

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