Abstract
In this paper, the problem of finite-time \({H_\infty }\) synchronization for complex dynamical networks with Markovian jump parameter is investigated. This purpose is concentrated on designing controller such that the obtain synchronization error system is finite-time \({H_\infty }\) synchronization. Based on the delay subinterval decomposition approach and linear matrix inequality approach, a new Lyapunov–Krasovskii functional is proposed to acquire the sufficient condition. Finally, numerical simulations are exploited to demonstrate our theoretical results.
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Ali, M. S., Saravanakumar, R., & Zhu, Q. X. (2015). Less conservation delay-dependent control of uncertain neural networks with discrete interval and distributed time-varying delays. Neurocomputing, 166, 84–95.
Balasubramaniam, P., & Chandran, R. (2011). Delay decomposition approach to stability analysis for uncertain fuzzy Hopfield neural networks with time-varying delay. Communications in Nonlinear Science and Numerical Simulation, 16, 2098–2108.
Chen, C., Li, L. X., Peng, H. P., et al. (2017). Finite time synchronization of memristor-based Cohen-Grossberg neural networks with mixed delays. PLoS ONE, 12(9), e0185007.
Chen, W. H., Jiang, Z. Y., Lu, X. M., & Luo, S. X. (2015). Synchronization for complex dynamical networks with coupling delays using distributed impulsive control. Nonlinear Analysis: Hybrid Systems, 17, 111–127.
Chen, Y. G., Bi, W. P., & Li, W. L. (2010). Stability analysis for neural networks with time-varying delay: A more general decomposition approach. Neurocomputing, 73, 853–857.
Cheng, J., Zhu, H., Zhong, S. M., Zeng, Y., & Dong, X. C. (2013). Finite-time control for a class of Markovian jump systems with mode-dependent time-varying delays via new Lyapunov functional. ISA Transactions, 52, 768–774.
Cheng, M. F., & Hu, H. P. (2011). Synchronization of impulsively-coupled complex switched networks. In Chinese control and decision conference (pp. 177–184).
Cui, W. X., Sun, S. Y., Fang, J. A., Xu, Y. L., & Zhao, L. D. (2014). Finite-time synchronization of Markovian jump complex networks with partially unknown transition rates. Journal of The Franklin Institute, 351, 2543–2561.
D’Addona, D. M., & Teti, R. (2013). Image data processing via neural networks for tool wear prediction. Science Direct, 12, 252–257.
Duan, W., Cai, C., Zou, Y., & You, J. (2013). Synchronization criteria for singular complex dynamical networks with delayed coupling and non-delayed coupling. Control Theory Applications, 30, 947–955.
Fei, Z., Gao, H., & Shi, P. (2009). New results on stabilization of Markovian jump systems with time delay. Automatica, 45, 2300–2306.
Jing, T. Y., Chen, F. Q., & Li, Q. H. (2015). Finite-time mixed outer synchronization of complex networks with time-varying delay and unknown parameters. Applied Mathematical Modelling, 39, 7734–7743.
Kalpana, M., Balasubramaniam, P., & Ratnavelu, K. (2015). Sirect delay decomposition approach to synchronization of chaotic fuzzy cellular neural networks with discrete, unbounded distributed delays and Markovian jumping parameters. Applied Mathematica and Computation, 254, 291–304.
Lakshmanan, S., Mathiyalagan, K., Park, J. H., Sakthivel, R., & Rihan, F. A. (2014). Delay-dependent state estimation of neural networks with mixed time-varying delays. Neurpcomputing, 129, 392–400.
Li, H. J. (2013). Cluster synchronization and state estimation for complex dynamical networks with mixed time delays. Applied Mathematical Modelling, 37, 7223–7244.
Li, D., & Cao, J. D. (2015). Finite-time synchronization of coupled networks with one single time-varying delay coupling. Neurocomputing, 166, 265–270.
Li, F., & Shen, H. (2015). Finite-time synchronization control for semi-Markov jump delayed neural networks with randomly occurring uncertainties. Neurpcomputing, 166, 447–454.
Li, Z. K., Duan, Z. S., & Chen, G. R. (2009). Disturbance rejection and pinning control of linear complex dynamical networks. Chinese Physics B, 18, 5228–5234.
Liu, P. L. (2013a). A delay decomposition approach to stability analysis of neutral systems with time-varying delay. Applied Mathematical Modelling, 37, 5013–5026.
Liu, P. L. (2013b). State feedback stabilization of time-varying delay uncertain system: A delay decomposition approach. Linear Algebra and Its Applications, 438, 2188–2209.
Liu, P. L. (2015). Delayed decomposition approach to the robust absolute stability of a Lur’e control system with time-varying delay. Applied Mathematical Modeling, 00, 1–13.
Liu, K., & Fridman, E. (2012). Networked-based stabilization via discontinuous Lyapunov functional. International Journal of Robust and Nonlinear Control, 22, 420–436.
Liu, X. H., Yu, X. H., & Xi, H. S. (2015). Finite-time synchronization of neural complex networks with Markovian switching based on pinning controller. Neurocomputing, 153, 148–158.
Lu, P. L., & Yang, Y. (2012). Synchronization of a class of complex networks. In Chinese control conference (pp. 1136–1141).
Ma, N. N., Liu, Z. B., & Chen, L. (2018). Robust and non-fragile finite time \({H_\infty }\) synchronization control for complex networks with uncertain inner coupling. Computational and Applied Mathematics, 37, 5395–5409.
Mei, J., Jiang, M. H., Xu, W. M., & Wang, B. (2013). Finite-time synchronization control of complex networks with time delay. Communications in Nonlinear Science and Numerical Simulation, 18, 2462–2478.
Revathi, V. M., Balasubramaniam, P., & Ratnavelu, K. (2016). Delay-dependent filtering for complex dynamical networks with time-varying delays in nonlinear function and network couplings. Signal Processing, 118, 122–132.
Shao, Y. Y., Liu, X. D., Sun, X., & Zhang, Q. L. (2014). A delay decomposition approach to admissibility for discrete-time singular delay systems. Information Sciences, 279, 893–905.
Shen, H., Park, J. H., Wu, Z. G., & Zhang, Z. Q. (2015). Finite-time synchronization for complex networks with semi-Markov jump topology. Communications in Nonlinear Science and Numerical Simulation, 24, 40–51.
Sun, Y. Z., Li, W., & Zhao, D. H. (2012). Finite-time stochastic outer synchronization between two complex dynamical networks with different topologies. Chao, 22, 023152.
Su, L., & Shen, H. (2015). Mixed/passive synchronization for complex dynamical networks with sampled-data control. Applied Mathematical and Computation, 259, 931–942.
Wang, H., & Xue, A. (2011). New stability criterion for singular time-delay systems and its application to partial element equivalent circuit. Control Theory Applications, 28, 1431–1435.
Wu, H. Q., Zhang, X. W., Li, R. X., & Yao, R. (2015). Finite-time synchronization of chaotic neural networks with mixed time-varying delays and stochastic disturbance. Memetic Computing, 7, 1–10.
Wu, L., Su, X., Shi, P., & Qiu, J. (2011). A new approach to stability analysis and stabilization of discrete-time T–S fuzzy time-varying delay systems. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 40, 273–286.
Xu, R. P., Kao, Y. G., & Gao, M. M. (2015). Finite-time synchronization of Markovian jump complex networks with generally uncertain transition rates. Journal of Biological Chemistry, 271, 14271–14279.
Xu, Y. H., Zhou, W. N., Fang, J. A., Xie, C. R., & Tong, D. B. (2016). Finite-time synchronization of the complex dynamical network with non-derivative and derivative coupling. Neurocomputing, 173, 1356–1361.
Yang, X. S., & Cao, J. D. (2010). Finite-time stochastic synchronization of complex networks. Applied Mathematical Modeling, 34, 3631–3641.
Yang, R., Zhang, Z., & Shi, P. (2010). Exponential stability on stochastic neural networks with discrete interval and distributed. IEEE Transactions on Neural Networks, 21, 169–175.
Zhang, X. M., & Han, Q. L. (2009). A delay decomposition approach to control of networked control systems. European Journal of Control, 5, 523–533.
Zhang, H. T., Yu, T., Sang, J. P., & Zou, X. W. (2014). Dynamic fluctuation model of complex networks with weight scaling behavior and its application to airport networks. Physica A, 39, 500–599.
Zheng, M. W., Li, L. X., Peng, H. P., et al. (2017). Finite-time projective synchronization of memristor-based delay fractional-order neural networks. Nonlinear Dynamics, 89, 2641–2655.
Zheng, M. W., Li, L. X., Peng, H. P., et al. (2018). Finite-time stability and synchronization of memristor-based fractional-order fuzzy cellular neural networks. Communications in Nonlinear Science and Numerical Simulation, 59, 2462–2478.
Zhu, J. W., & Yang, G. H. (2016). Robust dynamic output feedback synchronization for complex dynamical networks with disturbances. Neurocomputing, 175, 287–292.
Acknowledgements
This paper is supported by applied fundamental research (Major frontier projects) of Sichuan Province (16JC0314). The authors would like to thank the editor and anonymous reviewers for their many helpful comments and suggestions to improve the quality of this paper.
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Ma, N., Liu, Z. & Chen, L. Finite-Time \({H_\infty }\) Synchronization for Complex Dynamical Networks with Markovian Jump Parameter. J Control Autom Electr Syst 30, 75–84 (2019). https://doi.org/10.1007/s40313-018-00428-9
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DOI: https://doi.org/10.1007/s40313-018-00428-9