Skip to main content

Advertisement

SpringerLink
Log in

Adaptive Finite-Time Synchronization of Neutral Type Dynamical Network with Double Derivative Coupling

  • Published:
Neural Processing Letters Aims and scope Submit manuscript

Abstract

This paper discusses the problem of adaptive finite-time synchronization for neutral type dynamical network model with double derivative coupling. Based on the Lyapunov functional theory, inequality theorem, and adaptive control technique, some synchronization criteria of neutral type dynamical network are established by using adaptive finite-time control, which is different from the existence of finite-time synchronization of neutral type network using LMI and matrix equality constraint methods. Moreover, when the dynamics nodes of the neutral type network contain delay or no delay, the control gain of the response network are also provided. Finally, the effectiveness of the synchronization criteria proposed in this paper is verified by numerical simulations.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. Lu J, Ho DWC (2010) Globally exponential synchronization and synchronizability for general dynamical networks. IEEE Trans Syst Man Cybern Part B 40(2):350–361

    Article  Google Scholar 

  2. Lu J, Ding C, Lou J, Cao J (2015) Outer synchronization of partially coupled dynamical networks via pinning impulsive controllers. J Frankl Inst 352:5024–5041

    Article  MathSciNet  Google Scholar 

  3. Lu J, Kurths J, Cao J, Mahdavi N, Huang C (2012) Synchronization control for nonlinear stochastic dynamical networks: pinning impulsive strategy. IEEE Trans Neural Netw Learn Syst 23(2):285–292

    Article  Google Scholar 

  4. Tang Y, Wong W (2013) Distributed synchronization of coupled neural networks via randomly occurring control. IEEE Trans Neural Netw Learn Syst 24:435–447

    Article  Google Scholar 

  5. Tang Y, Gao H, Zou W, Kurths J (2013) Distributed synchronization in networks of agent systems with nonlinearities and random switchings. IEEE Trans Cybern 43:358–370

    Article  Google Scholar 

  6. Tang Y, Wang Z, Gao H, Swift S, Kurths J (2012) A constrained evolutionary computation method for detecting controlling regions of cortical networks. IEEE/ACM Trans Comput Biol Bioinform 9:1569–1581

    Article  Google Scholar 

  7. Mei G, Wu X, Ning D, Lu J (2016) Finite-time stabilization of complex dynamical networks via optimal control. Complexity 21:417–425

    Article  MathSciNet  Google Scholar 

  8. Lu R, Shi P, Su H, Wu Z, Lu J (2017) Synchronization of general chaotic neural networks with non-uniform sampling and packet missing: a switched system approach. IEEE Trans Neural Netw Learn Syst. https://doi.org/10.1109/TNNLS.2016.2636163

    Article  MathSciNet  Google Scholar 

  9. Zhang Y, Xu S, Chu Y, Lu J (2010) Robust global synchronization of complex networks with neutral-type delayed nodes. Appl Math Comput 216:768–778

    MathSciNet  MATH  Google Scholar 

  10. Liu X, Xi H (2014) Synchronization of neutral complex dynamical networks with Markovian switching based on sampled-data controller. Neurocomputing 139:163–179

    Article  Google Scholar 

  11. Wang J, Zhang H, Wang Z, Liang H (2015) Local stochastic synchronization for Markovian neutral-type complex networks with partial information on transition probabilities. Neurocomputing 167:474–487

    Article  Google Scholar 

  12. Zhou L, Wang Z, Zhou J, Zhou W (2016) Mean square synchronization of neural networks with Levy noise via sampled-data and actuator saturating controller. Neurocomputing 173:1235–1244

    Article  Google Scholar 

  13. Wang Y, Yang W, Xiao J, Zeng Z (2017) Impulsive multi-synchronization of coupled multistable neural networks with time-varying delay. IEEE Trans Neural Netw Learn Syst 28(7):1560–1571

    Article  MathSciNet  Google Scholar 

  14. Deng L, Wu Z, Wu Q (2013) Pinning synchronization of complex network with non- derivative and derivative coupling. Nonlinear Dyn 73:775–782

    Article  MathSciNet  Google Scholar 

  15. Xu Y, Zhou W, Fang J, Xie C, Tong D (2016) Finite-time synchronization of the complex dynamical network with non-derivative and derivative coupling. Neurocomputing 173:1356–1361

    Article  Google Scholar 

  16. Lam J, Gao H, Wang C (2007) Stability analysis for continuous systems with two additive time-varying delay components. Syst. Control Lett. 56:16–24

    Article  MathSciNet  Google Scholar 

  17. Wei H, Li R, Chen C, Tu Z (2016) Extended dissipative analysis for memristive neural networks with two additive time-varying delay components. Neurocomputing 216:429–438

    Article  Google Scholar 

  18. Hou M, Tan F, Duan G (2016) Finite-time passivity of dynamic systems. J Franklin Inst 353(18):4870–4884

    Article  MathSciNet  Google Scholar 

  19. Wang W, Li L, Peng H, Kurths J, Xiao J, Yang Y (2016) Finite-time anti-synchronization control of memristive neural networks with stochastic perturbations. Neural Process Lett 43(1):49–63

    Article  Google Scholar 

  20. Jing T, Chen F, Li Q (2015) Finite-time mixed outer synchronization of complex networks with time-varying delay and unknown parameters. Appl Math Model 39(23–24):7734–7743

    Article  MathSciNet  Google Scholar 

  21. Zhang L, Yang Y, Wang F, Sui X. (2017) Finite-time lag synchronization for memristive mixed delays neural networks with parameter mismatch. Neural Process Lett. https://doi.org/10.1007/s11063-017-9653-z

  22. Shen H, Park J, Wu Z (2014) Finite-time synchronization control for uncertain Markov jump neural networks with input constraints. Nonlinear Dyn 77(4):1709–1720

    Article  MathSciNet  Google Scholar 

  23. Wang X, Fang J, Mao H, Dai A (2015) Finite-time global synchronization for a class of Markovian jump complex networks with partially unknown transition rates under feedback control. Nonlinear Dyn 79:47–61

    Article  Google Scholar 

  24. Zhao H, Li L, Peng H, Kurths J, Xiao J, Yang Y (2017) Finite-time robust synchronization of memrisive neural network with perturbation. Neural Process Lett. https://doi.org/10.1007/s11063-017-9664-9

  25. Zhou C, Zhang W, Yang X, Xu C, Feng J (2017) Finite-Time Synchronization of Complex-Valued Neural Networks with Mixed Delays and Uncertain Perturbations. Neural Process Lett 46(1):271–291

    Article  Google Scholar 

  26. Mei J, Jiang M, Wang X, Han J, Wang S (2014) Finite-time synchronization of drive-response systems via periodically intermittent adaptive control. J Franklin Inst 351:2691–2710

    Article  MathSciNet  Google Scholar 

  27. Xu Y, Zhang J, Zhou W, Tong D (2017) Finite-time bounded synchronization of the growing complex network with non-delayed and delayed coupling. Discrete Dyn Nat Soc 2017, Article ID 6501583

  28. Liu B (2017) Finite-time stability of a class of CNNs with heterogeneous proportional delays and oscillating leakage coefficients. Neural Process Lett 45(1):109–119

    Article  Google Scholar 

  29. Cai S, He Q, Hao J, Liu Z (2010) Exponential synchronization of complex networks with nonidentical time-delayed dynamical nodes. Phys Lett A 374:2539–2550

    Article  MathSciNet  Google Scholar 

  30. Bhat S, Bernstein D (1998) Continuous finite-time stabilization of the translational and rotational double integrators. IEEE Trans Autom Control 43(11):678–682

    Article  MathSciNet  Google Scholar 

  31. Wu Z, Shi P, Su H, Chu J (2014) Local synchronization of chaotic neural networks with sampled-data and saturating actuators. IEEE Trans Cybern 44:2635–2645

    Article  Google Scholar 

  32. Rakkiyappan R, Sakthivel N, Cao J (2015) Stochastic sampled-data control for synchronization of complex dynamical networks with control packet loss and additive time-varying delays. Neural Netw 66:46–63

    Article  Google Scholar 

  33. Hardy G, Littlewood J, Polya G (1952) Inequalities. Cambridge University Press, Cambridge

    MATH  Google Scholar 

  34. Lü J, Chen G (2002) A new chaotic attractor coined. Int J Bifurc Chaos 12:659–661

    Article  MathSciNet  Google Scholar 

  35. Xu Y, Lu Y, Zhou W, Fang J (2016) Bounded synchronization of the general complex dynamical network with delay feedback controller. Nonlinear Dyn 84:661–667

    Article  MathSciNet  Google Scholar 

  36. Mei G, Wu X, Wang Y, Hu M, Lu J, Chen G (2017) Compressive-sensing-based structure identification for multilayer networks. IEEE Trans Cybern. https://doi.org/10.1109/TCYB.2017.2655511

    Article  Google Scholar 

Download references

Acknowledgements

This work is supported by the National Natural Science Foundation of China (61673221, 61673257, and 11701287), the Youth Fund Project of the Humanities and Social Science Research for the Ministry of Education of China (14YJCZH173), Top-notch Academic Programs Project of Jiangsu Higher Education Institutions (Jiangsu Province Office, no. [2015]1, PPZY2015B104), Applied Economics of key Sequence Disciplines of Jiangsu Higher Education Institutions (Jiangsu Province Office, no. [2014]37), “Qing-Lan Engineering” Foundation of Jiangsu Higher Education Institutions, and A Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD).

Author information

Authors and Affiliations

  1. School of Finance, Nanjing Audit University, Nanjing, 211815, Jiangsu, China

    Yuhua Xu

  2. College of Information Science and Technology, Donghua University, Shanghai, 201620, China

    Wuneng Zhou

  3. Electrical Engineering Automation, Qilu University of Technology, Jinan, 250353, China

    Hongqian Lu

  4. College of Science, Nanjing Audit University, Nanjing, 211815, Jiangsu, China

    Chengrong Xie

  5. College of Electronic and Electrical Engineering, Shanghai University of Engineering Science, Shanghai, 201620, China

    Dongbing Tong

Authors
  1. Yuhua Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Wuneng Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hongqian Lu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Chengrong Xie
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Dongbing Tong
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Chengrong Xie.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Xu, Y., Zhou, W., Lu, H. et al. Adaptive Finite-Time Synchronization of Neutral Type Dynamical Network with Double Derivative Coupling. Neural Process Lett 48, 1175–1186 (2018). https://doi.org/10.1007/s11063-017-9772-6

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11063-017-9772-6

Keywords

Search

Navigation