Skip to main content

Finite-Time Synchronization of Uncertain Complex Networks with Nonidentical Nodes Based on a Special Unilateral Coupling Control

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10262))

Abstract

This note investigates finite-time synchronization (FTS) between two uncertain complex networks based on a special unilateral coupling control method. The two networks contain nonidentical nodes, time-varying coupling delayed, unknown parameters and uncertain topological structure. According to the finite-time stability theory and LaSalle’s principle, an effective unilateral coupling control scheme and corresponding adaptive laws are proposed to guarantee the FTS. Simultaneously, the unknown parameters are estimated successfully and the weight values of uncertain topology can automatically adaptive to the suitable value. Finally, simulation results are shown the correctness of the theoretical method.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Arenas, A., Díaz-Guilera, A., Kurths, J., Moreno, Y., Zhou, C.: Synchronization in complex networks. Phys. Rep. 469, 93–153 (2008)

    Article  MathSciNet  Google Scholar 

  2. Suykens, J.A.K., Osipov, G.V.: Introduction to focus issue: synchronization in complex networks. Chaos 18, 037101-4 (2008)

    Google Scholar 

  3. Yang, X., Cao, J.: Exponential synchronization of delayed neural networks with discontinuous activations. IEEE Trans. Circ. Syst. I 60, 2431–2439 (2013)

    MathSciNet  Google Scholar 

  4. Guo, Z., Yang, S., Wang, J.: Global exponential synchronization of multiple memristive neural networks with time delay via nonlinear coupling. IEEE Trans. Neural Netw. Learn. Syst. 26, 1300–1311 (2015)

    Article  MathSciNet  Google Scholar 

  5. Liu, H., Cheng, L., Tan, M., Hou, Z.G., Wang, Y.P.: Distributed exponential finite-time coordination of multi-agent systems: containment control and consensus. Int. J. Control 88, 237–247 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  6. Boccaletti, S., Latora, V., Moreno, Y., Chavezf, M., Hwanga, D.U.: Complex networks: Structure and dynamics. Phys. Rep. 424, 175–308 (2006)

    Article  MathSciNet  Google Scholar 

  7. Mei, J., Jiang, M., Wang, J.: Finite-time structure identification and synchronization of drive-response systems with uncertain parameter. Commun. Nonlinear Sci. Numer. Simul. 18, 999–1015 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  8. Sun, Y., Li, W., Zhao, D.: Finite-time stochastic outer synchronization between two complex dynamical networks with different topologies. Chaos 22, 023152-7 (2012)

    Google Scholar 

  9. Yang, X., Cao, J., Lu, J.: Stochastic synchronization of complex networks with nonidentical nodes via hybrid adaptive and impulsive control. IEEE Trans. Circ. Syst. I 59, 371–384 (2012)

    Article  MathSciNet  Google Scholar 

  10. Lee, D., Yoo, W., Ji, D., Park, J.: Integral control for synchronization of complex dynamical networks with unknown non-identical nodes. Appl. Math. Comput. 224, 140–149 (2013)

    MathSciNet  MATH  Google Scholar 

  11. Chen, W., Jiang, Z., Zhong, J., Lu, X.: On designing decentralized impulsive controllers for synchronization of complex dynamical networks with nonidentical nodes and coupling delays. J. Franklin Inst. 351, 4084–4110 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  12. Abdurahman, A., Jiang, H., Hu, C., Teng, Z.: Parameter identification based on finite-time synchronization for Cohen-Grossberg neural networks with time-varying delays. Nonlinear Anal. 20, 348–366 (2015)

    Article  MathSciNet  Google Scholar 

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

    Article  MathSciNet  Google Scholar 

  14. Liu, H., Lu, J., Lü, J., Hill, D.: Structure identification of uncertain general complex dynamical networks with time delay. Automatica 45, 1799–1807 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  15. Che, Y., Li, R., Han, C., Cui, S., Wang, J., Wei, X., Deng, B.: Topology identification of uncertain nonlinearly coupled complex networks with delays based on anticipatory synchronization. Chaos 23, 013127-7 (2013)

    Google Scholar 

  16. Khalil, H., Grizzle, J.: Nonlinear Systems. Prentice Hall, Upper Saddle River (2002)

    Google Scholar 

  17. Han, M., Zhang, M., Zhang, Y.: Projective synchronization between two delayed networks of different sizes with nonidentical nodes and unknown parameters. Neurocomputing 171, 605–614 (2016)

    Article  Google Scholar 

  18. Xu, Y., Zhou, W., Fang, J., Lu, H.: Structure identification and adaptive synchronization of uncertain general complex dynamical networks. Phys. Lett. A 374, 272–278 (2009)

    Article  MATH  Google Scholar 

Download references

Acknowledgments

This work was supported by the National Natural Science Foundation of China (No. 61374154).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Min Han .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Zhang, M., Han, M. (2017). Finite-Time Synchronization of Uncertain Complex Networks with Nonidentical Nodes Based on a Special Unilateral Coupling Control. In: Cong, F., Leung, A., Wei, Q. (eds) Advances in Neural Networks - ISNN 2017. ISNN 2017. Lecture Notes in Computer Science(), vol 10262. Springer, Cham. https://doi.org/10.1007/978-3-319-59081-3_20

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-59081-3_20

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59080-6

  • Online ISBN: 978-3-319-59081-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics