Finite time Synchronization of Inertial Memristive Neural Networks with Time Varying Delay

  • Yajing Pang Hebei University of Science and Technology
  • Shengmei Dong

Abstract

Finite time synchronization control of inertial memristor-based neural networks with varying delay is considered. In view of drive and response concept, the sufficient conditions to ensure finite time synchronization issue of inertial memristive neural networks is given. Based on Lyapunov finite time asymptotic theory, a kind of feedback controllers is designed for inertial memristorbased neural networks to realize the finite time synchronization. Based on Lyapunov stability theory, close loop error system can be proved finite time and fixed time stable. Finally, illustrative example is given to illustrate the effectiveness of theoretical results.

References

[1] Cao, J.; Wang, J. (2003). Global asymptotic stability of a general class of recurrent neural networks with time-varying delays, IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications, 50(1), 34-44, 2003.
https://doi.org/10.1109/TCSI.2002.807494

[2] Chu, X.; Xu, L.; Hu, H. (2020). Exponential quasi-synchronization of conformable fractional-order complex dynamical networks, Chaos, Solitons & Fractals, 140, 110268, 2020.
https://doi.org/10.1016/j.chaos.2020.110268

[3] Cui, W.; Wang, Z.; Jin, W. (2020). Fixed-time synchronization of Markovian jump fuzzy cellular neural networks with stochastic disturbance and time-varying delays, Fuzzy Sets and Systems, in press, 2020.
https://doi.org/10.1016/j.fss.2020.05.007

[4] Fadel, M.Z.; Rabie, M.G.; Youssef, A.M. (2019). Modeling, simulation and control of a fly-by-wire flight control system using classical PID and modified PI-D controllers, Journal Européen des Systèmes Automatisés, 52(3), 267-276, 2019.
https://doi.org/10.18280/jesa.520307

[5] Gan, Y.; Liu, C.; Peng, H.; Liu, F.; Rao, H. (2020). Anti-synchronization for periodic bam neural networks with Markov scheduling protocol, Neurocomputing, 417, 585-592, 2020.
https://doi.org/10.1016/j.neucom.2020.08.015

[6] Ke, L. (2020). Synchronization control of high-order inertial Hopfield neural network with time delay, Revue d'Intelligence Artificielle, 34(5), 595-600, 2020.
https://doi.org/10.18280/ria.340509

[7] Lee, T.H.; Lim, C.P.; Nahavandi, S.; Park, J.H. (2018). Network-based synchronization of T-S fuzzy chaotic systems with asynchronous samplings, Journal of the Franklin Institute, 355(13), 5736-5758, 2018.
https://doi.org/10.1016/j.jfranklin.2018.05.023

[8] Li, J.Y.; Zhang, B.; Lu, R.; Xu, Y.; Rao, H.X. (2020). Synchronization for markovian coupled neural networks with partial mode observation: The finite-time case, Journal of the Franklin Institute, 357(17), 12767-12786, 2020.
https://doi.org/10.1016/j.jfranklin.2020.09.029

[9] Lü, L.; Wei, Q.; Jia, H.; Tian, S.; Xu, Z.; Zhao, L.; Xu, Z.; Xu, X. (2019). Parameter identification and synchronization between uncertain delay networks based on the coupling technology, Physica A: Statistical Mechanics and its Applications, 534, 120713, 2019.
https://doi.org/10.1016/j.physa.2019.03.078

[10] Lu, X.; Wu, Q.; Zhou, Y.; Ma, Y.; Song, C.; Ma, C. (2019). A dynamic swarm firefly algorithm based on chaos theory and Max-Min distance algorithm, Traitement du Signal, 36(3), 227-231, 2019.
https://doi.org/10.18280/ts.360304

[11] Pan, C.; Bao, H. (2020). Exponential synchronization of complex-valued memristor-based delayed neural networks via quantized intermittent control, Neurocomputing, 404, 317-328, 2020.
https://doi.org/10.1016/j.neucom.2020.04.097

[12] Pecora, L.M.; Carroll, T.L. (1990). Synchronization in Chaotic Systems, Physical Review Letters, 64(8), 821, 1990.
https://doi.org/10.1103/PhysRevLett.64.821

[13] Pi, J.; Zhang, W.; Zhang, S.; Pi, C.; Xie, C. (2019). A separated adaptive control strategy for different conditions based on flexible dynamics equation of robot manipulator, Journal Européen des Systèmes Automatisés, 52(6), 575-585, 2019.
https://doi.org/10.18280/jesa.520605

[14] Rafikov, M.; Balthazar, J.M. (2008). On control and synchronization in chaotic and hyperchaotic systems via linear feedback control, Communications in Nonlinear Science and Numerical Simulation, 13(7), 1246-1255, 2008.
https://doi.org/10.1016/j.cnsns.2006.12.011

[15] Schijven, D.; Stevelink, R.; McCormack, M.; van Rheenen, W.; Luykx, J.J.; Koeleman, B.P.; Veldink, J.H.; Project MinE ALS Project MinE ALS GWAS Consortium. (2020). Analysis of shared common genetic risk between amyotrophic lateral sclerosis and epilepsy, Neurobiology of Aging, 92, 153-e1, 2020.
https://doi.org/10.1016/j.neurobiolaging.2020.04.011

[16] Song, X.; Man, J.; Song, S.; Zhang, Y.; Ning, Z. (2020). Finite/fixed-time synchronization for Markovian complex-valued Memristive neural networks with reaction-diffusion terms and its application, Neurocomputing, 414, 131-142, 2020.
https://doi.org/10.1016/j.neucom.2020.07.024

[17] Sun, B.; Cao, Y.; Guo, Z.; Yan, Z.; Wen, S. (2020). Synchronization of discrete-time recurrent neural networks with time-varying delays via quantized sliding mode control, Applied Mathematics and Computation, 375, 125093, 2020.
https://doi.org/10.1016/j.amc.2020.125093

[18] Wang, H.D. (2010). A synchronous transmission method for array signals of sensor network under resonance technology, Traitement du Signal, 37(4), 579-584, 2020.
https://doi.org/10.18280/ts.370405

[19] Wang, W.; Fan, Y. (2015). Synchronization of Arneodo chaotic system via backstepping fuzzy adaptive control, Optik, 126(20), 2679-2683, 2015.
https://doi.org/10.1016/j.ijleo.2015.06.071

[20] Wang, W.; Tian, K.; Zhang, J. (2020). Dynamic modelling and adaptive control of automobile active suspension system, Journal Européen des Systèmes Automatisés, 53(2), 297-303, 2020.
https://doi.org/10.18280/jesa.530218

[21] Yang, L.; Huang, T.; Deng, L.; Zeng, Y.; Huang, S. (2019). Analysis on chaotic mechanism of direct-drive permanent magnet synchronous generators based on Lyapunov stability theory, European Journal of Electrical Engineering, 21(6), 531-537, 2019.
https://doi.org/10.18280/ejee.210607

[22] Zhang, Y.; Han, Q.L. (2012). Network-based synchronization of delayed neural networks, IEEE Transactions on Circuits and Systems I: Regular Papers, 60(3), 676-689, 2013.
https://doi.org/10.1109/TCSI.2012.2215793

[23] Zheng, B.; Hu, C.; Yu, J.; Jiang, H. (2020). Finite-time synchronization of fully complex-valued neural networks with fractional-order, Neurocomputing, 373, 70-80, 2020.
https://doi.org/10.1016/j.neucom.2019.09.048
Published
2021-04-16
How to Cite
PANG, Yajing; DONG, Shengmei. Finite time Synchronization of Inertial Memristive Neural Networks with Time Varying Delay. INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL, [S.l.], v. 16, n. 4, apr. 2021. ISSN 1841-9844. Available at: <http://univagora.ro/jour/index.php/ijccc/article/view/4215>. Date accessed: 17 sep. 2021. doi: https://doi.org/10.15837/ijccc.2021.3.4215.