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Practical fixed time active control scheme for synchronization of a class of chaotic neural systems with external disturbances

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  • Su, Haipeng
  • Luo, Runzi
  • Huang, Meichun
  • Fu, Jiaojiao

Abstract

The objective in this work is to consider the practical fixed-time synchronization of delayed chaotic neural networks interfered by uncertain impacts. Firstly, to derive the sufficient conditions of fixed time stability, a novel practical fixed-time stability criterion, which can be viewed as the generalization of the existed results, is set up. Then, by means of the obtained stability criterion, we develop an effective fixed time control approach to attain the practical network synchronization within a limited time. In our synchronization scheme, the error state trajectories of two chaotic neural networks move forward to the small domain of zero in a short time freeing from the initial states. Besides, different from the traditional methodologies that dealt with the external disturbances, the chatter phenomenon can be avoided since our proposed controllers don’t contain the signum functions. Finally, the effectiveness of the obtained theoretical results and synchronization scheme are testified by conducting the simulations.

Suggested Citation

  • Su, Haipeng & Luo, Runzi & Huang, Meichun & Fu, Jiaojiao, 2022. "Practical fixed time active control scheme for synchronization of a class of chaotic neural systems with external disturbances," Chaos, Solitons & Fractals, Elsevier, vol. 157(C).
    • Handle: RePEc:eee:chsofr:v:157:y:2022:i:c:s0960077922001278
    DOI: 10.1016/j.chaos.2022.111917
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    References listed on IDEAS

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    1. Yuhua Xu & Jincheng Zhang & Wuneng Zhou & Dongbing Tong, 2017. "Finite-Time Bounded Synchronization of the Growing Complex Network with Nondelayed and Delayed Coupling," Discrete Dynamics in Nature and Society, Hindawi, vol. 2017, pages 1-7, January.
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    Cited by:

    1. Meichun Huang & Yunong Zhang, 2024. "Zhang Neuro-PID Control for Generalized Bi-Variable Function Projective Synchronization of Nonautonomous Nonlinear Systems with Various Perturbations," Mathematics, MDPI, vol. 12(17), pages 1-25, August.
    2. Jia, Wenwen & Xie, Jingu & Guo, Haihua & Wu, Yongbao, 2024. "Intermittent boundary control for fixed-time stability of reaction–diffusion systems," Chaos, Solitons & Fractals, Elsevier, vol. 181(C).
    3. Abinandhitha, R. & Monisha, S. & Sakthivel, R. & Manikandan, R. & Saat, S., 2023. "Proportional integral observer-based input–output finite-time stabilization for chaotic semi-Markov jump fuzzy systems," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).
    4. Luo, Runzi & Song, Zijun & Liu, Shuai, 2023. "Fixed-time observed synchronization of chaotic system with all state variables unavailable in some periods," Chaos, Solitons & Fractals, Elsevier, vol. 170(C).
    5. Gao, Zifan & Zhang, Dawei & Zhu, Shuqian, 2023. "Hybrid event-triggered synchronization control of delayed chaotic neural networks against communication delay and random data loss," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).
    6. Liu, Xinxiao & Wang, Lijie & Liu, Yang, 2023. "Fixed-time nonlinear-filter-based consensus control for nonlinear multiagent systems," Chaos, Solitons & Fractals, Elsevier, vol. 177(C).
    7. Yao, Qijia & Alsaade, Fawaz W. & Al-zahrani, Mohammed S. & Jahanshahi, Hadi, 2023. "Fixed-time neural control for output-constrained synchronization of second-order chaotic systems," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).

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