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Predictive-based control of complex dynamic networks

Author

Listed:
  • Arbid, Mahmoud
  • Teffahi, Abdelkader
  • Boukabou, Abdelkrim
  • Bounar, Amel

Abstract

This paper addresses the problem of designing a robust controller for a class of complex dynamical networks (CDNs). This class of CDNs is characterized by a scale-free typical structure with Rossler and Lorenz-type nodes. Direct control of every node in a CDN with a large number of nodes might be unnecessary. Based on the concept of pinning control of continuous-time chaotic systems and the matrix measure theory, some simple stability criteria are derived to guarantee the asymptotic stability of the system states such that all the system states of the closed-loop system converge towards the desired unstable equilibrium points. Consequently, the proposed controller developed here for scale-free networks can be employed to handle a broader class of CDNs with different types of nodes. Numerical simulations are provided to show the effectiveness of the proposed control method.

Suggested Citation

  • Arbid, Mahmoud & Teffahi, Abdelkader & Boukabou, Abdelkrim & Bounar, Amel, 2023. "Predictive-based control of complex dynamic networks," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).
    • Handle: RePEc:eee:chsofr:v:172:y:2023:i:c:s0960077923004289
    DOI: 10.1016/j.chaos.2023.113527
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    References listed on IDEAS

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    1. Xiao-Bing Hu & Adrian V. Gheorghe & Mark S. Leeson & Supeng Leng & Julien Bourgeois & Xiaobo Qu, 2016. "Risk and Safety of Complex Network Systems," Mathematical Problems in Engineering, Hindawi, vol. 2016, pages 1-3, January.
    2. Wang, Xiao Fan & Chen, Guanrong, 2002. "Pinning control of scale-free dynamical networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 310(3), pages 521-531.
    3. Réka Albert & Hawoong Jeong & Albert-László Barabási, 1999. "Diameter of the World-Wide Web," Nature, Nature, vol. 401(6749), pages 130-131, September.
    4. Boukabou, Abdelkrim & Mekircha, Naim, 2012. "Generalized chaos control and synchronization by nonlinear high-order approach," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 82(11), pages 2268-2281.
    5. Kemih, Karim, 2009. "Control of nuclear spin generator system based on passive control," Chaos, Solitons & Fractals, Elsevier, vol. 41(4), pages 1897-1901.
    6. Nannan Ma & Zhibin Liu & Lin Chen, 2019. "Synchronisation for complex dynamical networks with hybrid coupling time-varying delays via pinning adaptive control," International Journal of Systems Science, Taylor & Francis Journals, vol. 50(8), pages 1661-1676, June.
    7. Zou, Yanli & Chen, Guanrong, 2009. "Choosing effective controlled nodes for scale-free network synchronization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(14), pages 2931-2940.
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