Indian Journal of Physics

, Volume 93, Issue 9, pp 1181–1186 | Cite as

Delay feedback impulsive control of a time-delay nonlinear complex financial networks

  • Guoliang Cai
  • Zhiyin ZhangEmail author
  • Gaihong Feng
  • Qiaoling Chen
Original Paper


Complex networks theory has been applied in various field. Many scholars devoted it to financial system and established a nonlinear complex financial networks model. In this paper, delay feedback impulsive control of a time-delay nonlinear complex financial networks is discussed. Based on the Lyapunov stability theory and the impulsive differential equation stability theory, the asymptotic stability and ideal equilibrium point of complex financial networks are obtained. As a result, the complex financial networks have reached a new level of sustainable stability. The simulation results show the feasibility and effectiveness of the proposed control method and verify the correctness of the proposed theoretical analysis.


Impulsive control Nonlinear complex financial networks Time-delay feedback control Stability 


05.45.-a 05.45.Xt 89.65.Gh 



This work was supported by the National Social Science Foundation of China (No. 18BJL073), the Key Scientific Research Projects of Higher Education Institutions of Henan Province (No. 18A120013), the Social Science Foundation of Education Department of Henan Province (No. 2019-ZZJH-202), and the Young Key Teachers Program of Higher Education Institutions of Henan Province (No. 2017GGJS193). Especially, thanks for the support of Jiangsu University and Zhengzhou Shengda University.


  1. [1]
    H J Li, Z J Ning, Y H Yin and Y Tang Commun. Nonlinear Sci. Numer. Simul. 18 194 (2013)ADSMathSciNetCrossRefGoogle Scholar
  2. [2]
    H Han, L Y Wu and N N Song Acta. Phys. Sin. 63 138901 (2014)Google Scholar
  3. [3]
    T Y Lv, X F Pu, W Y Xie and S B Huang Acta. Phys. Sin. 61 170512 (2012)Google Scholar
  4. [4]
    X F Wang and G R Chen Phys. A 310 521 (2002)MathSciNetCrossRefGoogle Scholar
  5. [5]
    L H Wang, W Ding and Chen D Phys. Lett. A 374 1440 (2010)ADSCrossRefGoogle Scholar
  6. [6]
    S Zheng Math. Probl. Eng. 2012 501843 (2012)Google Scholar
  7. [7]
    G L Cai, S Q Jiang, S M Cai and LX Tian Nonlinear Dyn. 80 503 (2015)CrossRefGoogle Scholar
  8. [8]
    S M Cai, P P Zhou and Z R Liu Nonlinear Anal. Hybrid Syst. 18 134 (2015)MathSciNetCrossRefGoogle Scholar
  9. [9]
    S Q Jiang, G L Cai, S M Cai, L X Tian and X B Lu Commun. Nonlinear Sci. Numer. Simul. 28 194 (2015)ADSMathSciNetCrossRefGoogle Scholar
  10. [10]
    Z L Wang, Y L Jiang and H L Li Complexity 21 125(2016)MathSciNetGoogle Scholar
  11. [11]
    Q J Zhang and J C Zhao Nonlinear Dyn. 67 2519 (2012)CrossRefGoogle Scholar
  12. [12]
    Y Q Yang and J D Cao Nonlinear Anal. RWA 11 1650 (2010)CrossRefGoogle Scholar
  13. [13]
    T D Ma and F Y Zhao Chin. Phys. B 23 120504 (2014)ADSCrossRefGoogle Scholar
  14. [14]
    X R Shi, Z L Wang and L X Han Nonlinear Dyn. 88 2747 (2017)CrossRefGoogle Scholar
  15. [15]
    S Zheng Complexity 21 547(2016)ADSMathSciNetCrossRefGoogle Scholar
  16. [16]
    L L Zhang and G L Cai J. Appl. Anal. Comp. 7 79 (2017)ADSGoogle Scholar
  17. [17]
    Q J Wu, J Zhou and L Xiang Appl. Math. Lett. 23 143 (2008)CrossRefGoogle Scholar
  18. [18]
    H J Yu, G L Cai and Y X Li Nonlinear Dyn. 67 2171 (2012)CrossRefGoogle Scholar
  19. [19]
    L L Zhang and G L Cai Lect. Notes Comput. Sci. 9502 447 (2015)CrossRefGoogle Scholar

Copyright information

© Indian Association for the Cultivation of Science 2019

Authors and Affiliations

  1. 1.Institute of Applied MathematicsZhengzhou Shengda University of Economics, Business and ManagementZhengzhouPeople’s Republic of China
  2. 2.Nonlinear Scientific Research CenterJiangsu UniversityZhenjiangPeople’s Republic of China

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