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Decentralized Adaptive Event-Triggered Synchronization of Neutral Neural Networks with Time-Varying Delays

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Abstract

In this work, the adaptive event-triggered synchronization in a class of master–slave neutral neural networks with time-varying delay is studied. The design of decentralized event-triggered scheme is proposed, which only utilizes local available information to determine the released instants from multiple sensors to a centralized controller. Different from existing ones, the triggering thresholds depend on real-time performance of controlled system. Together with some novel Lyapunov terms, an augmented Lyapunov–Krasovskii functional is constructed, in which the interconnection between time delays can be fully utilized. In particular, a less conservative condition on controller gain is obtained in terms of linear matrix inequalities. Finally, the derived results are verified by resorting to two numerical examples.

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Authors and Affiliations

  1. School of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106, People’s Republic of China

    Tao Li & Yaobao Yu

  2. School of Information Science and Technology, Nanjing Forestry University, Nanjing, 210042, People’s Republic of China

    Ting Wang

  3. School of Automation, Southeast University, Nanjing, 210096, People’s Republic of China

    Shumin Fei

Authors
  1. Tao Li
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  2. Yaobao Yu
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  3. Ting Wang
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  4. Shumin Fei
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Correspondence to Tao Li.

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Li, T., Yu, Y., Wang, T. et al. Decentralized Adaptive Event-Triggered Synchronization of Neutral Neural Networks with Time-Varying Delays. Circuits Syst Signal Process 38, 874–890 (2019). https://doi.org/10.1007/s00034-018-0889-2

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  • DOI: https://doi.org/10.1007/s00034-018-0889-2

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