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机构地区:[1]College of Information Science and Technology,Donghua University [2]Institute of Textiles and Clothing,Hong Kong Polytechnic University [3]Continue Education School,Shanghai Jiaotong University
出 处:《Chinese Physics B》2011年第4期187-196,共10页中国物理B(英文版)
基 金:supported by the National Natural Science Foundation of China (Grant No. 60874113);the Research Fund for the Doctoral Program of Higher Education of China (Grant No. 200802550007);the Key Foundation Project of Shanghai,China(Grant No. 09JC1400700);the Key Creative Project of Shanghai Education Community,China (Grant No. 09ZZ66);the National Basic Research Development Program of China (Grant No. 2010CB731400);the Research Grants Council of the Hong Kong Special Administrative Region,China (Grant No. PolyU 5212/07E)
摘 要:In this paper, the pinning synchronization problem of stochastic delayed complex network (SDCN) is investigated by using a novel hybrid pinning controller. The proposed hybrid pinning controller is composed of adaptive controller and impulsive controller, where the two controllers are both added to a fraction of nodes in the network. Using the Lyapunov stability theory and the novel hybrid pinning controller, some sufficient conditions are derived for the exponential synchronization of such dynamical networks in mean square. Two numerical simulation examples are provided to verify the effectiveness of the proposed approach. The simulation results show that the proposed control scheme has a fast convergence rate compared with the conventional adaptive pinning method.In this paper, the pinning synchronization problem of stochastic delayed complex network (SDCN) is investigated by using a novel hybrid pinning controller. The proposed hybrid pinning controller is composed of adaptive controller and impulsive controller, where the two controllers are both added to a fraction of nodes in the network. Using the Lyapunov stability theory and the novel hybrid pinning controller, some sufficient conditions are derived for the exponential synchronization of such dynamical networks in mean square. Two numerical simulation examples are provided to verify the effectiveness of the proposed approach. The simulation results show that the proposed control scheme has a fast convergence rate compared with the conventional adaptive pinning method.
关 键 词:time-varying delay pinning impulsive synchronization stochastic complex network exponential synchronization
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