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Tracking control for the dynamic links of discrete-time complex dynamical network via state observer

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  • Liu, Lizhi
  • Wang, Yinhe
  • Gao, Zilin

Abstract

In this paper, a class of discrete-time complex dynamical networks with time-varying links is regarded to be composed of the nodes subsystem and links subsystem which are mutually coupled. In the existing literatures on complex dynamical networks, the emphasizes is synchronization or stabilization of nodes, the dynamic behaviors of the links between nodes are always ignored. It is noted that the state of links is very important to the networks in practical, such as, the tension value of webs in web-winding system, the relationships between individuals in social network, therefore, discussing the tracking control problem for links subsystem is also of practical significance. Considering the state of links is difficult to be measured accurately in practice applications, this makes it difficult to design the controller. In view of this, a state observer is proposed for the links subsystem modeled mathematically by the Riccati matrix difference equation in this paper. And then the control scheme is proposed for the links subsystem by employing the state observer such that the links subsystem asymptotically converging to the given target. Finally, the simulations are used to show the validity of the method in this paper.

Suggested Citation

  • Liu, Lizhi & Wang, Yinhe & Gao, Zilin, 2020. "Tracking control for the dynamic links of discrete-time complex dynamical network via state observer," Applied Mathematics and Computation, Elsevier, vol. 369(C).
    • Handle: RePEc:eee:apmaco:v:369:y:2020:i:c:s0096300319308495
    DOI: 10.1016/j.amc.2019.124857
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    References listed on IDEAS

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    1. Zhang, Lili & Wang, Yinhe & Huang, Yuanyuan & Chen, Xuesong, 2015. "Delay-dependent synchronization for non-diffusively coupled time-varying complex dynamical networks," Applied Mathematics and Computation, Elsevier, vol. 259(C), pages 510-522.
    2. Wu, Zhaoyan, 2015. "Synchronization of discrete dynamical networks with non-delayed and delayed coupling," Applied Mathematics and Computation, Elsevier, vol. 260(C), pages 57-62.
    3. Wang, Jing & Hu, Xiaohui & Wei, Yunliang & Wang, Zhen, 2019. "Sampled-data synchronization of semi-Markov jump complex dynamical networks subject to generalized dissipativity property," Applied Mathematics and Computation, Elsevier, vol. 346(C), pages 853-864.
    4. Wang, Jing & Ru, Tingting & Xia, Jianwei & Wei, Yunliang & Wang, Zhen, 2019. "Finite-time synchronization for complex dynamic networks with semi-Markov switching topologies: An H∞ event-triggered control scheme," Applied Mathematics and Computation, Elsevier, vol. 356(C), pages 235-251.
    5. Hu, Xiaohui & Xia, Jianwei & Wei, Yunliang & Meng, Bo & Shen, Hao, 2019. "Passivity-based state synchronization for semi-Markov jump coupled chaotic neural networks with randomly occurring time delays," Applied Mathematics and Computation, Elsevier, vol. 361(C), pages 32-41.
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