Kybernetika 62 no. 1, 77-98, 2026

Prescribed-time pinning control for delayed memristive neural networks via event-triggered strategy

Xiaowei Meng, Yanlin Zhu, Hua Zhang and Quanjun WuDOI: 10.14736/kyb-2026-1-0077

Abstract:

This paper investigates the issues of prescribed-time synchronization for memristive neural networks with time-varying delay by event-triggered pinning control. To conserve resources and enhance control efficiency, two event-based control schemes and the measurement error function are obtained. Then, using Lyapunov stability theory and inequality techniques, some sufficient conditions are obtained to ensure the prescribed time synchronization of the response system and the drive system. Furthermore, under the two event trigger conditions, a positive lower bound on the inter-event time is derived respectively to ensure that Zeno behavior can be excluded during the whole time span except the prescribed settling time. Finally, numerical simulations are provided to illustrate the effectiveness of the obtained theoretical results.

Keywords:

event-triggered control, pinning control, prescribed-time synchronization, memristive neural networks, Zeno behavior

Classification:

93C10, 34D06, 34D20

paper.pdf

References:

  1. W. Ai, J. Zhai and S. Fei: Global finite-time stabilization for a class of stochastic nonlinear systems by dynamic state feedback. Kybernetika 49 (2013), 590-600.   DOI:10.1007/s12035-013-8544-1
  2. X. Chen, H. Yu and F. Hao: Prescribed-time event-triggered bipartite consensus of multiagent systems. IEEE Trans. Cybern. 52 (2022), 2589-2598.   DOI:10.1109/TCYB.2020.3004572
  3. L. Chua: Memristor-the missing circuit element. IEEE Trans. Circuit Theory 18 (1971), 507-519.   DOI:10.1109/TCT.1971.1083337
  4. M. Dong, S. Wen, Z. Zeng, Z. Yan and T. Huang: Sparse fully convolutional network for face labeling. Neurocomputing 331 (2019), 465-472.   DOI:10.1016/j.neucom.2018.11.079
  5. Y. Fan, X. Huang, H. Shen and J. Cao: Switching event-triggered control for global stabilization of delayed memristive neural networks: An exponential attenuation scheme. Neural Netw. 117 (2019), 216-224.   DOI:10.1016/j.neunet.2019.05.014
  6. S. Gong, Z. Guo, S. Wen and T. Huang: Finite-time and fixed-time synchronization of coupled memristive neural networks with time delay. IEEE Trans. Cybern. 51 (2021), 2944-2955.   DOI:10.1109/TCYB.2019.2953236
  7. Z. Guo, S. Yang and J. Wang: Global synchronization of memristive neural networks subject to random disturbances via distributed pinning control. Neural Netw. 84 (2016), 67-69.   DOI:10.1016/j.jbankfin.2016.01.010
  8. X. Jia, H. Li and X. Chi: Prescribed-time consensus of integrator-type multi-agent systems via sampled-data control. IEEE Trans. Circuits Syst. II Exp. Briefs 71 (2024), 3413-3417.   DOI:10.1109/TCSII.2024.3361078
  9. H. Liu, J. A. Lu, J. Lu and D. J. Hill: Structure identification of uncertain general ¨ complex dynamical networks with time delay. Automatica 45 (2009), 1799-1807.   DOI:10.1016/j.automatica.2009.03.022
  10. D. Lyu, M. Sun and Q. Jia: Event-based prescribed-time synchronization of directed dynamical networks with lipschitzian nodal dynamics. IEEE Trans. Circuits Syst. II Exp. Briefs 69 (2021), 1847-1851.   DOI:10.1109/TCSII.2021.3134683
  11. Y. Pershin and M. D. Ventra: Experimental demonstration of associative memory with memristive neural networks. Neural Netw. 23 (2010), 881-886.   DOI:10.1016/j.neunet.2010.05.001
  12. D. B. Strukov, G. S. Snider, D. R. Stewart and R. S. Williams: The missing memristor found. Nature 453 (2008), 80-83.   DOI:10.1038/nature06932
  13. H. Wang, S. Duan, T. Huang and J. Tan: Synchronization of memristive delayed neural networks via hybrid impulsive control. Neurocomputing 267 (2017), 615-623.   DOI:10.1016/j.neucom.2017.06.028
  14. K. Wang, Z. Teng and H. Jiang: Adaptive synchronization of neural networks with time-varying delay and distributed delay. Physica A 387 (2008), 631-642.   DOI:10.1016/j.physa.2007.09.016
  15. S. Wang and J. Jian: Predefined-time synchronization of fractional-order memristive competitive neural networks with time-varying delays. Chaos Solitons Fractals 174 (2023), 113790.   DOI:10.1016/j.chaos.2023.113790
  16. Z. Peng, Z. Zhang, R. Luo, Y. Kuang, J. Hu, H. Cheng and B. K. Ghosh: Event-triggered optimal control of completely unknown nonlinear systems via identifier-critic learning. Kybernetika 59 (2023), 365-391.   DOI:10.14736/kyb-2023-3-0365
  17. X. Wang, J. H. Park, Z. Liu and H. Yang: Dynamic event-triggered control for GSES of memristive neural networks under multiple cyber-attacks. IEEE Trans. Neural Netw. Learn. Syst. 35 (2024), 7602-7611.   DOI:10.1109/TNNLS.2022.3217461
  18. Y. Wang, Y. Song, D. J. Hill and M.Krstic: Prescribed-time consensus and containment control of networked multiagent systems. IEEE Trans. Cybern. 49 (2018), 1138-1147.   DOI:10.1109/TCYB.2017.2788874
  19. Q. Wu, J. Zhou and X. Lan: Impulses-induced exponential stability in recurrent delayed neural networks. Neurocomputing 74 {(2011)}, 3204-3211.   DOI:10.1016/j.neucom.2011.05.001
  20. W. Xu, S. Zhu, X. Fang and W. Wang: Adaptive anti-synchronization of memristor-based complex-valued neural networks with time delays. Phys A 535 (2019), 122427.   DOI:10.1016/j.physa.2019.122427
  21. Z. Yan, W. Liu, S. Wen and Y. Yang: Multi-label image classification by feature attention network. IEEE Access 7 (2019), 98005-98013.   DOI:10.1109/ACCESS.2019.2929512
  22. L. Yan, Z. Wang, Y. Zhang and Y. Fan: Sampled-data control for mean-square exponential stabilization of memristive neural networks under deception attacks. Chaos Solitons Fractals 174 (2023), 113787.   DOI:10.1016/j.chaos.2023.113787
  23. J. Yang, G. Chen, S. Zhu, S. Wen and J. Hu: Fixed/prescribed-time synchronization of BAM memristive neural networks with time-varying delays via convex analysis. Neural Netw. 163 (2023), 53-63.   DOI:10.1016/j.neunet.2023.03.031
  24. S. Yang, C. Li and T. Huang: Exponential stabilization and synchronization for fuzzy model of memristive neural networks by periodically intermittent control. Neural Netw. 75 (2016), 162-172.   DOI:10.1016/j.expthermflusci.2016.02.003
  25. Z. Yang, B. Luo, D. Liu and Y. Li: Pinning synchronization of memristor-based neural networks with time-varying delays. Neural Netw. 93 (2017), 143-151.   DOI:10.1016/j.neunet.2017.05.003
  26. H. Zhang, Z. Liu, G. B. Huang and Z. Wang: Novel weighting-delay based stability criteria for recurrent neural networks with time-varying delay. IEEE Trans. Neur. Netw. 21 (2009), 91-106.   DOI:10.1109/TNN.2009.2034742
  27. J. Zhou and Q. Wu: Exponential stability of impulsive delayed linear differential equations. IEEE Trans. Circuits Syst. II, Exp. Briefs 56 (2009), 744-48.   DOI:10.1109/TCSII.2009.2027947
  28. J. Zhou, Q. Wu and L. Xiang: Pinning complex delayed dynamical networks by a single impulsive controller. IEEE Trans. Circuits Syst. I Regul. Pap. 58 (2011), 2882-2893.   DOI:10.1109/TCSI.2011.2161363
  29. W. Zhu and Z. P. Jiang: Event-based leader-following consensus of multi-agent systems with input time delay. IEEE Trans. Autom. Control 60 (2014), 1362-1367.   DOI:10.1109/TAC.2014.2357131
  30. Y. Zhu and M. Jiang: Prescribed-time synchronization of inertial memristive neural networks with time-varying delays. AIMS Math. 10 (2025), 9900-9916.   DOI:10.3934/math.2025453