Abstract
In this paper, synchronization of both non-identical unknown network and identical known network can be considered. Based on Lyapunov stability theory, for the case of non-identical or identical network, synchronization criteria between drive-response networks are obtained, and both the uncertain parameters and unknown coupling configuration matrix are be identified or constructed. Meanwhile, the coupling matrix may be free. The proposed synchronization scheme is simple and easy to realize. Finally, three illustrative examples show the effectiveness of presented control schemes.
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References
Strogatz, S.H.: Exploring complex networks. Nature 410, 268–276 (2001)
Nian, F.: Adaptive coupling synchronization in complex network with uncertain boundary. Nonlinear Dyn. 70, 861–870 (2012)
Zhang, Q., Lu, J., Lü, J., Member, S., Tse, C.K.: Adaptive feedback synchronization of a general complex dynamical network with delayed nodes. IEEE Trans. Circuits Syst. II Express Briefs 55(2), 183–187 (2008)
Gong, D., Zhang, H., Wang, Z., Huang, B.: Pinning synchronization for a general complex networks with multiple time-varying coupling delays. Neural Process. Lett. 35, 221–231 (2012)
Guo, W., Austin, F., Chen, S., Sun, W.: Pinning synchronization of the complex networks with non-delayed and delayed coupling. Phys. Lett. A 373, 1565–1572 (2009)
Lu, J., Kurths, J., Mahdavi, N., Cao, J.: Impulsive control for the synchronization of stochastic dynamical networks. In: Nonlinear Dynamics and Synchronization (INDS) & 16th Int’l Symposium on Theoretical Electrical Engineering, 1–5 (2011)
Li, C., Chen, L., Aihara, K.: Impulsive control of stochastic systems with applications in chaos synchronization, and neural networks. Chaos 18(2) (2008)
Tang, Y., Leung, S.Y.S., Wong, W.K., Fang, J.: Impulsive pinning synchronization of stochastic discrete-time networks. Neurocomputing 73, 2132–2139 (2010)
Lu, J., Cao, J.: Synchronization-based approach for parameters identification in delayed chaotic neural networks. Physica A 382, 672–682 (2007)
Khalil, H.K.: Nonlinear Systems. Prentice Hall PTR (2002)
Lü, J., Chen, G., Cheng, D., Celikovsky, S.: Bridge the gap between the Lorenz system and the Chen system. Int. J. Bifurc. Chaos 12, 2917–2926 (2002)
Acknowledgements
This work was supported by the National Natural Science Foundation of China (No. 11672104), the Chair Professor of Lotus Scholars Program in Hunan Province (No. XJT2015408). The authors also would like to thank the support from the scientific research project of Hengyang Normal University (No. 18D24).
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Chen, Z., Tian, X., Lei, T., Chen, J. (2021). Outer Synchronization Between Complex Delayed Networks with Both Uncertain Parameters and Unknown Topological Structure. In: Liu, Q., Liu, X., Li, L., Zhou, H., Zhao, HH. (eds) Proceedings of the 9th International Conference on Computer Engineering and Networks . Advances in Intelligent Systems and Computing, vol 1143. Springer, Singapore. https://doi.org/10.1007/978-981-15-3753-0_14
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DOI: https://doi.org/10.1007/978-981-15-3753-0_14
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