This paper investigated the quasi-synchronization of nonlinear systems with parameter mismatch and time-varying delays via the event-triggered impulsive control (ETIC) approach, which integrates impulsive control and event-triggered control. The instances of impulsive activation were determined by an event-triggered mechanism based on a particular condition that depends on the system states. By employing the comparison principle for impulsive systems and the formula for variable parameters, we established the exact synchronization error bound and derived sufficient conditions for achieving quasi-synchronization. Furthermore, we proved the absence of Zeno behavior in the controlled system under the ETIC mechanism. Finally, we gave an example to verify that the theoretical results are valid under the proposed ETIC strategy.
Citation: Biwen Li, Yujie Liu. Quasi-synchronization of nonlinear systems with parameter mismatch and time-varying delays via event-triggered impulsive control[J]. AIMS Mathematics, 2025, 10(2): 3759-3778. doi: 10.3934/math.2025174
This paper investigated the quasi-synchronization of nonlinear systems with parameter mismatch and time-varying delays via the event-triggered impulsive control (ETIC) approach, which integrates impulsive control and event-triggered control. The instances of impulsive activation were determined by an event-triggered mechanism based on a particular condition that depends on the system states. By employing the comparison principle for impulsive systems and the formula for variable parameters, we established the exact synchronization error bound and derived sufficient conditions for achieving quasi-synchronization. Furthermore, we proved the absence of Zeno behavior in the controlled system under the ETIC mechanism. Finally, we gave an example to verify that the theoretical results are valid under the proposed ETIC strategy.
[1] |
Q. Y. Yang, Y. L. Yu, X. L. Li, C. Chen, F. L. Lewis, Adaptive distributed synchronization of heterogeneous multi-agent systems over directed graphs with time-varying edge weights, J. Franklin Inst., 358 (2021), 2434–2452. http://doi.org/10.1016/j.jfranklin.2021.01.018 doi: 10.1016/j.jfranklin.2021.01.018
![]() |
[2] |
T. Yang, L. O. Chua, Impulsive stabilization for control and synchronization of chaotic systems: theory and application to secure communication, IEEE Trans. Circuits Syst. I: Fundam. Theory Appl., 44 (1997), 976–988. http://doi.org/10.1109/81.633887 doi: 10.1109/81.633887
![]() |
[3] |
Y. Sheng, H. Zhang, Z. G. Zeng, Synchronization of reaction diffusion neural networks with dirichlet boundary conditions and infinite delays, IEEE Trans Cybern., 47 (2017), 3005–3017. http://doi.org/10.1109/TCYB.2017.2691733 doi: 10.1109/TCYB.2017.2691733
![]() |
[4] |
Z. Y. Zhang, B. Luo, D. R. Liu, Y. H. Li, Pinning synchronization of memristor-based neural networks with time-varying delays, Neural Networks, 93 (2017), 143–151. https://doi.org/10.1016/j.neunet.2017.05.003 doi: 10.1016/j.neunet.2017.05.003
![]() |
[5] |
X. Z. Liu, K. X. Zhang, W. C. Xie, Pinning impulsive synchronization of reaction-diffusion neural networks with time-varying delays, IEEE Trans. Neur. Net. Learn. Syst., 28 (2017), 1055–1067. https://doi.org/10.1109/TNNLS.2016.2518479 doi: 10.1109/TNNLS.2016.2518479
![]() |
[6] |
R. Q. Lu, P. Shi, H. G. Su, Z. G. Wu, J. Q. Lu, Pinning impulsive synchronization of reaction-diffusion neural networks with time-varying delays, IEEE Trans. Neur. Net. Learn. Syst., 29 (2018), 523–533. https://doi.org/10.1109/TNNLS.2016.2636163 doi: 10.1109/TNNLS.2016.2636163
![]() |
[7] |
J. D. Cao, J. Q. Lu, Adaptive synchronization of neural networks with or without time-varying delay, Chaos, 16 (2006), 013133. https://doi.org/10.1063/1.2178448 doi: 10.1063/1.2178448
![]() |
[8] |
Y. F. Zhou, H. Zhang, Z. G. Zeng, Quasi-synchronization of delayed memristive neural networks via a hybrid impulsive control, IEEE Trans. Syst. Man, Cybern.: Syst., 51 (2021), 1954–1965. https://doi.org/10.1109/TSMC.2019.2911366 doi: 10.1109/TSMC.2019.2911366
![]() |
[9] |
W. Zhu, Q. H. Zhou, D. D. Wang, Consensus of linear multi-agent systems via adaptive event-based protocols, Neurocomputing, 318 (2018), 175–181. https://doi.org/10.1016/j.neucom.2018.08.050 doi: 10.1016/j.neucom.2018.08.050
![]() |
[10] |
S. B. Ding, Z. S. Wang, N. N. Rong, Intermittent control for quasi-synchronization of delayed discrete-time neural networks, IEEE Trans Cybern., 51 (2021), 862–873. https://doi.org/10.1109/TCYB.2020.3004894 doi: 10.1109/TCYB.2020.3004894
![]() |
[11] |
H. T. Zhu, J. Q. Lu, J. G. Lou, Event-triggered impulsive control for nonlinear systems: the control packet loss case, IEEE Trans. Circuits Syst. II: Express Briefs, 69 (2022), 3204–3208. https://doi.org/10.1109/TCSII.2022.3140346 doi: 10.1109/TCSII.2022.3140346
![]() |
[12] |
L. Z. Zhang, Y. Y. Li, J. G. Lou, J. Q. Lu, Bipartite asynchronous impulsive tracking consensus for multi-agent systems, Front. Inform. Technol. Electron. Eng., 23 (2022), 1522–1532. https://doi.org/10.1631/FITEE.2100122 doi: 10.1631/FITEE.2100122
![]() |
[13] |
X. Z. Hou, H. Q. Wu, J. D. Cao, Observer-based prescribed-time synchronization and topology identification for complex networks of piecewise-smooth systems with hybrid impulses, Comp. Appl. Math., 43 (2024), 180. https://doi.org/10.1007/s40314-024-02701-x doi: 10.1007/s40314-024-02701-x
![]() |
[14] |
S. Y. Dong, X. Z. Liu, S. M. Zhong, K. B. Shi, H. Zhu, Practical synchronization of neural networks with delayed impulses and external disturbance via hybrid control, Neural Networks, 157 (2023), 54–64. https://doi.org/10.1016/j.neunet.2022.09.025 doi: 10.1016/j.neunet.2022.09.025
![]() |
[15] |
R. Kumar, S. Sarkar, S. Das, J. D. Cao, Projective synchronization of delayed neural networks with mismatched parameters and impulsive effects, IEEE Trans. Neur. Net. Learn. Syst., 31 (2020), 1211–1221. https://doi.org/10.1109/TNNLS.2019.2919560 doi: 10.1109/TNNLS.2019.2919560
![]() |
[16] |
J. T. Sun, Y. P. Zhang, Q. D. Wu, Less conservative conditions for asymptotic stability of impulsive control systems, IEEE Trans. Autom. Control, 48 (2003), 829–831. https://doi.org/10.1109/TAC.2003.811262 doi: 10.1109/TAC.2003.811262
![]() |
[17] |
G. M. Zhuang, Y. Q. Liu, J. W. Xia, X. P. Xie, Normalized P-D and intermittent hybrid $H_{\infty}$ control for delayed descriptor systems via impulsive-inputs-dependent conditions, IEEE Trans. Autom. Sci. Eng., 63 (2024), 3125–3134. https://doi.org/10.1109/TASE.2024.3389983 doi: 10.1109/TASE.2024.3389983
![]() |
[18] |
Z. Tang, J. H. Park, J. W. Feng, Impulsive effects on quasi-synchronization of neural networks with parameter mismatches and time-varying delay, IEEE Trans. Neur. Net. Learn. Syst., 29 (2018), 908–919. https://doi.org/10.1109/TNNLS.2017.2651024 doi: 10.1109/TNNLS.2017.2651024
![]() |
[19] |
Y. F. Zhou, Z. G. Zeng, Event-triggered impulsive control on quasi-synchronization of memristive neural networks with time-varying delays, Neural Networks, 110 (2019), 55–65. https://doi.org/10.1016/j.neunet.2018.09.014 doi: 10.1016/j.neunet.2018.09.014
![]() |
[20] |
S. Wen, Z. G. Zeng, M. Z. Q. Chen, T. W. Huang, Synchronization of switched neural networks with communication delays via the event-triggered control, IEEE Trans. Neur. Net. Learn. Syst., 28 (2017), 2334–2343. https://doi.org/10.1109/TNNLS.2016.2580609 doi: 10.1109/TNNLS.2016.2580609
![]() |
[21] |
Y. T. Cao, S. B. Wang, Z. Y. Guo, T. W. Huang, S. P. Wen, Synchronization of memristive neural networks with leakage delay and parameters mismatch via event-triggered control, Neural Networks, 119 (2019), 178–189. https://doi.org/10.1016/j.neunet.2019.08.011 doi: 10.1016/j.neunet.2019.08.011
![]() |
[22] |
Y. Y. Ni, Z. Wang, Y. J. Fan, J. Q. Lu, S. Hao, A switching memory-based event-trigger scheme for synchronization of Lur'e systems with actuator saturation: a hybrid Lyapunov method, IEEE Trans. Neur. Net. Learn. Syst., 35 (2024), 13963–13974. https://doi.org/10.1109/TNNLS.2023.3273917 doi: 10.1109/TNNLS.2023.3273917
![]() |
[23] |
Y. Y. Ni, Z. Wang, Y. J. Fan, J. Q. Lu, S. Hao, Secure stabilization of networked Lur'e systems Suffering from DoS attacks: a resilient memory-based event-trigger mechanism, IEEE Trans. Inf. Forensics Secur., 19 (2024), 4658–4669. https://doi.org/10.1109/TIFS.2024.3384055 doi: 10.1109/TIFS.2024.3384055
![]() |
[24] |
X. Q. Zhao, H. Q. Wu, J. D. Cao, L. F. Wang, Prescribed-time synchronization for complex dynamic networks of piecewise smooth systems: a hybrid event-triggering control approach, Qual. Theory Dyn. Syst., 24 (2025), 11. https://doi.org/10.1007/s12346-024-01166-x doi: 10.1007/s12346-024-01166-x
![]() |
[25] |
X. Q. Zhao, H. Q. Wu, J. D. Cao, Practical finite-time synchronization for Lur'e systems with performance constraint and actuator faults: a memory-based quantized dynamic event-triggered control strategy, Appl. Math. Comput., 487 (2025), 129108. https://doi.org/10.1016/j.amc.2024.129108 doi: 10.1016/j.amc.2024.129108
![]() |
[26] |
D. V. Dimarogonas, E. Frazzoli, K. H. Johansson, Distributed event-triggered control for multi-agent systems, IEEE Trans. Autom. Control, 57 (2012), 1291–1297. https://doi.org/10.1109/TAC.2011.2174666 doi: 10.1109/TAC.2011.2174666
![]() |
[27] |
W. L. Lu, Y. J. Han, T. P. Chen, Synchronization in networks of linearly coupled dynamical systems via event-triggered diffusions, IEEE Trans. Neur. Net. Learn. Syst., 26 (2015), 3060–3069. https://doi.org/10.1109/TNNLS.2015.2402691 doi: 10.1109/TNNLS.2015.2402691
![]() |
[28] | Y. A. Meng, G. M. Zhuang, Y. Q. Wang, J. Feng, Observer-based switching-like adaptive-triggered resilient coordination control of discrete singular systems under DI attacks with uncertain occurrence probabilities, Int. J. Robust Nonlinear Control, 2024. https://doi.org/10.1002/rnc.7775 |
[29] |
J. Lunze, D. Lehmann, A state-feedback approach to event-based control, Automatica, 46 (2010), 211–215. https://doi.org/10.1016/j.automatica.2009.10.035 doi: 10.1016/j.automatica.2009.10.035
![]() |
[30] |
S. P. Wen, X. H. Yu, Z. G. Zeng, J. J. Wang, Event-triggering load frequency control for multiarea power systems with communication delays, IEEE Trans. Ind. Electron., 63 (2016), 1308–1317. https://doi.org/10.1109/TIE.2015.2399394 doi: 10.1109/TIE.2015.2399394
![]() |
[31] |
K. Ding, Q. X. Zhu, Intermittent quasi-synchronization criteria of chaotic delayed neural networks with parameter mismatches and stochastic perturbation mismatches via Razumikhin-type approach, Neurocomputing, 365 (2019), 314–324. https://doi.org/10.1016/j.neucom.2019.07.077 doi: 10.1016/j.neucom.2019.07.077
![]() |
[32] |
Y. T. Cao, S. P. Wen, M. Z. Q. Chen, T. W. Huang, Z. G. Zeng, New results on anti-synchronization of switched neural networks with time-varying delays and lag signals, Neural Networks, 81 (2016), 52–58. https://doi.org/10.1016/j.neunet.2016.05.004 doi: 10.1016/j.neunet.2016.05.004
![]() |
[33] |
H. N. Zheng, N. X. Yu, W. Zhu, Quasi-synchronization of drive–response systems with parameter mismatch via event-triggered impulsive control, Neural Networks, 161 (2023), 1–8. https://doi.org/10.1016/j.neunet.2023.01.020 doi: 10.1016/j.neunet.2023.01.020
![]() |
[34] |
W. L. He, F. Qian, J. Lam, G. R. Chen, Q. L. Han, J. Kurths, Quasi-synchronization of heterogeneous dynamic networks via distributed impulsive control: error estimation, optimization and design, Automatica, 62 (2015), 249–262. https://doi.org/10.1016/j.automatica.2015.09.028 doi: 10.1016/j.automatica.2015.09.028
![]() |
[35] |
Y. B. Zhao, H. Q. Wu, Fixed/Prescribed stability criterions of stochastic system with time-delay, AIMS Math., 9 (2024), 14425–14453. https://doi.org/10.3934/math.2024701 doi: 10.3934/math.2024701
![]() |
[36] |
Y. Wan, J. D. Cao, G. H. Wen, Quantized synchronization of chaotic neural networks with scheduled output feedback control, IEEE Trans. Neur. Net. Learn. Syst., 28 (2017), 2638–2647. https://doi.org/10.1109/TNNLS.2016.2598730 doi: 10.1109/TNNLS.2016.2598730
![]() |
[37] |
W. Zhu, D. D. Wang, L. Liu, G. Feng, Event-based impulsive control of continuous-time dynamic systems and its application to synchronization of memristive neural networks, IEEE Trans. Neur. Net. Learn. Syst., 29 (2018), 3599–3609. https://doi.org/10.1109/TNNLS.2017.2731865 doi: 10.1109/TNNLS.2017.2731865
![]() |
[38] |
C. D. Li, G. R. Chen, X. F. Liao, Z. P. Fan, Chaos quasisynchronization induced by impulses with parameter mismatches, Chaos, 16 (2006), 023102. https://doi.org/10.1063/1.2179648 doi: 10.1063/1.2179648
![]() |
[39] |
P. F. Curran, L. O. Chua, Absolute stability theory and the synchronization problem, Int. J. Bifurcat. Chaos, 7 (1997), 1375–1382. https://doi.org/10.1142/S0218127497001096 doi: 10.1142/S0218127497001096
![]() |
[40] |
Q. Xiao, Z. K. Huang, Z. G. Zeng, Passivity analysis for memristor-based inertial neural networks with discrete and distributed delays, IEEE Trans. Syst. Man Cybern.: Syst., 49 (2019), 375–385. https://doi.org/10.1109/TSMC.2017.2732503 doi: 10.1109/TSMC.2017.2732503
![]() |
[41] |
H. G. Zhang, T. D. Ma, G. B. Huang, Z. L. Wang, Robust global exponential synchronization of uncertain chaotic delayed neural networks via dual-stage impulsive control, IEEE Trans. Syst. Man. Cybern., 40 (2021), 831–844. https://doi.org/10.1109/TSMCB.2009.2030506 doi: 10.1109/TSMCB.2009.2030506
![]() |