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Integrated L∞ anti-disturbance synchronization control for switched neural networks with unknown delays

Author

Listed:
  • Chang, Wenting
  • Sang, Hong
  • Guo, Liangdong
  • Wu, Libing
  • Dimirovski, Georgi M.

Abstract

This research is concerned with the integrated L∞ anti-disturbance synchronization control problem for continuous-time switched neural networks (SNNs). Different from the relevant synchronization results about SNNs, multiple disturbances and unknown delays are simultaneously addressed in a uniform framework. By constructing the novel Lyapunov function and the ameliorative combined switching strategy, an L∞ performance analysis framework with less conservativeness is then established, where each individual subnetwork is unnecessary to possess a prescribed L∞ performance index. By designing an appropriate disturbance observer and transforming the delay-dependent neuron activation function into a bounded disturbance, an integrated L∞ anti-disturbance synchronization control paradigm is also presented on the basis of the proposed analysis framework. Finally, three illustrative examples are employed to substantiate the applicability and superiority of the developed theoretical results.

Suggested Citation

  • Chang, Wenting & Sang, Hong & Guo, Liangdong & Wu, Libing & Dimirovski, Georgi M., 2024. "Integrated L∞ anti-disturbance synchronization control for switched neural networks with unknown delays," Chaos, Solitons & Fractals, Elsevier, vol. 179(C).
  • Handle: RePEc:eee:chsofr:v:179:y:2024:i:c:s0960077924000262
    DOI: 10.1016/j.chaos.2024.114475
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    References listed on IDEAS

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    1. Arik, Sabri, 2005. "Global robust stability analysis of neural networks with discrete time delays," Chaos, Solitons & Fractals, Elsevier, vol. 26(5), pages 1407-1414.
    2. Maharajan, C. & Raja, R. & Cao, Jinde & Rajchakit, G. & Alsaedi, Ahmed, 2018. "Novel results on passivity and exponential passivity for multiple discrete delayed neutral-type neural networks with leakage and distributed time-delays," Chaos, Solitons & Fractals, Elsevier, vol. 115(C), pages 268-282.
    3. Manivannan, R. & Samidurai, R. & Cao, Jinde & Alsaedi, Ahmed & Alsaadi, Fuad E., 2018. "Stability analysis of interval time-varying delayed neural networks including neutral time-delay and leakage delay," Chaos, Solitons & Fractals, Elsevier, vol. 114(C), pages 433-445.
    4. Vadivel, R. & Hammachukiattikul, P. & Gunasekaran, Nallappan & Saravanakumar, R. & Dutta, Hemen, 2021. "Strict dissipativity synchronization for delayed static neural networks: An event-triggered scheme," Chaos, Solitons & Fractals, Elsevier, vol. 150(C).
    5. Karnan, A. & Nagamani, G., 2023. "Event-triggered extended dissipative synchronization for delayed neural networks with random uncertainties," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).
    6. Syed Ali, M. & Balasubramaniam, P., 2009. "Global exponential stability of uncertain fuzzy BAM neural networks with time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 42(4), pages 2191-2199.
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