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Event-triggered control for coupled reaction–diffusion complex network systems with finite-time synchronization

Author

Listed:
  • Luo, Yiping
  • Yao, Yuejie
  • Cheng, Zifeng
  • Xiao, Xing
  • Liu, Hanyu

Abstract

In this paper, a class of coupled nonlinear reaction–diffusion complex network system are investigated with finite-time synchronization based on the event-triggered control. The study aims to develop nonlinear complex network systems with partial differential terms under Dirichlet’s boundary conditions by combining the distributed event-triggered control protocol with the Lyapunov stability theorem, Green formula, matrix inequality, and partial differential equation theory. Several sufficient conditions for the system to achieve finite-time synchronization with or without time delay are obtained. Furthermore, the upper bound of time can be estimated to achieve synchronization. Finally, numerical simulation is used to prove the effectiveness of the theory.

Suggested Citation

  • Luo, Yiping & Yao, Yuejie & Cheng, Zifeng & Xiao, Xing & Liu, Hanyu, 2021. "Event-triggered control for coupled reaction–diffusion complex network systems with finite-time synchronization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 562(C).
    • Handle: RePEc:eee:phsmap:v:562:y:2021:i:c:s0378437120306403
    DOI: 10.1016/j.physa.2020.125219
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    References listed on IDEAS

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    1. Wang, Aijuan & Liao, Xiaofeng & Dong, Tao, 2018. "Finite-time event-triggered synchronization for reaction–diffusion complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 111-120.
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    4. Dong, Tao & Wang, Aijuan & Zhu, Huiyun & Liao, Xiaofeng, 2018. "Event-triggered synchronization for reaction–diffusion complex networks via random sampling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 495(C), pages 454-462.
    5. Zhang, Weiwei & Cao, Jinde & Wu, Ranchao & Chen, Dingyuan & Alsaadi, Fuad E., 2018. "Novel results on projective synchronization of fractional-order neural networks with multiple time delays," Chaos, Solitons & Fractals, Elsevier, vol. 117(C), pages 76-83.
    6. Yi-Ping Luo & Li Shu & Bi-Feng Zhou, 2017. "Global Exponential Synchronization of Nonlinearly Coupled Complex Dynamical Networks with Time-Varying Coupling Delays," Complexity, Hindawi, vol. 2017, pages 1-10, August.
    7. R. Saravanakumar & M. Syed Ali & H. R. Karimi, 2017. "Robust control of uncertain stochastic Markovian jump systems with mixed time-varying delays," International Journal of Systems Science, Taylor & Francis Journals, vol. 48(4), pages 862-872, March.
    8. Zhang, Jianmei & Wu, Jianwei & Bao, Haibo & Cao, Jinde, 2018. "Synchronization analysis of fractional-order three-neuron BAM neural networks with multiple time delays," Applied Mathematics and Computation, Elsevier, vol. 339(C), pages 441-450.
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    Cited by:

    1. Jiang, Tingting & Zhang, Yuping & Zeng, Yong & Zhong, Shouming & Shi, Kaibo & Cai, Xiao, 2021. "Finite-time analysis for networked predictive control systems with induced time delays and data packet dropouts," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    2. Hongkun Ma & Chengdong Yang, 2022. "Exponential Synchronization of Hyperbolic Complex Spatio-Temporal Networks with Multi-Weights," Mathematics, MDPI, vol. 10(14), pages 1-11, July.
    3. Serrano, Fernando E. & Ghosh, Dibakar, 2022. "Robust stabilization and synchronization in a network of chaotic systems with time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 159(C).

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