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Strict dissipativity synchronization for delayed static neural networks: An event-triggered scheme

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  • Vadivel, R.
  • Hammachukiattikul, P.
  • Gunasekaran, Nallappan
  • Saravanakumar, R.
  • Dutta, Hemen

Abstract

This article addresses the investigation of strict dissipativity synchronization for a class of static neural networks under an event-triggered scheme. An event-triggered scheme is recommended, it can upgrade the exhibition of system dynamics and diminishes the network communication burden at the same time. Firstly, an appropriate Lyapunov-Krasovskii functional (LKF) with double and triple integral terms with the details on both lower and upper bounds of the delay is completely designed. Secondly, under the single and double Auxillary function-based integral inequalities (SAFBII and DAFBII, respectively) and generalized free weight matrix approach, a new class of delay-dependent adequate condition is proposed, so that the error system is (Q,S,R)−γ− strict dissipative. A resilient distributed event-triggered control scheme is developed by this criterion in terms of linear matrix inequalities (LMIs). At last, simulation examples are provided to demonstrate the performance of the derived results.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:chsofr:v:150:y:2021:i:c:s096007792100566x
    DOI: 10.1016/j.chaos.2021.111212
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    6. Sun, Meng & Zhuang, Guangming & Ma, Qian & Wang, Yanqian, 2024. "Dynamic PDC and HMM-based asynchronous output feedback strict dissipative control for nonlinear singular incomplete jumping systems with actuator saturation," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).
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    8. Luo, Mei & Wang, JinRong & Meng, Deyuan, 2023. "Stochastic convergence problems on switching networks: An event-triggered method," Chaos, Solitons & Fractals, Elsevier, vol. 170(C).
    9. Yang, Wei & Cui, Guozeng & Ma, Qian & Ma, Jiali & Tao, Chongben, 2022. "Finite-time adaptive event-triggered command filtered backstepping control for a QUAV," Applied Mathematics and Computation, Elsevier, vol. 423(C).
    10. Gu, Yang & Shao, Yiyu & Li, Liwei & Shen, Mouquan, 2024. "Event-triggered fault tolerant control for Markov jump systems via a proportional–integral intermediate estimator," Chaos, Solitons & Fractals, Elsevier, vol. 180(C).
    11. 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).
    12. Saravanan Shanmugam & Rajarathinam Vadivel & Nallappan Gunasekaran, 2023. "Finite-Time Synchronization of Quantized Markovian-Jump Time-Varying Delayed Neural Networks via an Event-Triggered Control Scheme under Actuator Saturation," Mathematics, MDPI, vol. 11(10), pages 1-24, May.
    13. Saravanakumar, Ramasamy & Datta, Rupak & Cao, Yang, 2022. "New insights on fuzzy sampled-data stabilization of delayed nonlinear systems," Chaos, Solitons & Fractals, Elsevier, vol. 154(C).
    14. Liu, Haoliang & Zhang, Taixiang & Li, Xiaodi, 2021. "Event-triggered control for nonlinear systems with impulse effects," Chaos, Solitons & Fractals, Elsevier, vol. 153(P1).
    15. Zhang, Xiulan & Shi, Jiangteng & Liu, Heng & Chen, Fangqi, 2024. "Adaptive fuzzy event-triggered cooperative control for fractional-order delayed multi-agent systems with unknown control direction," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 220(C), pages 552-566.
    16. Karnan, A. & Nagamani, G., 2023. "Event-triggered extended dissipative synchronization for delayed neural networks with random uncertainties," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).

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