scholarly journals Adaptive-Impulsive Control of the Projective Synchronization in Drive-Response Complex Dynamical Networks with Time-Varying Coupling

2012 ◽  
Vol 2012 ◽  
pp. 1-12 ◽  
Author(s):  
Song Zheng

This paper investigates the projective synchronization (PS) of drive-response time-varying coupling complex dynamical networks with time delay via an adaptive-impulsive controlling method, in which the weights of links are time varying. Based on the stability analysis of impulsive control system, sufficient conditions for the PS are derived, and a hybrid controller, that is, an adaptive feedback controller with impulsive control effects, is designed. Numerical simulations are performed to verify the correctness and effectiveness of theoretical result.

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Song Zheng

The problem of projective synchronization of drive-response coupled dynamical network with delayed system nodes and multiple coupling time-varying delays is investigated. Some sufficient conditions are derived to ensure projective synchronization of drive-response coupled network under the impulsive controller by utilizing the stability analysis of the impulsive functional differential equation and comparison theory. Numerical simulations on coupled time delay Lorenz chaotic systems are exploited finally to illustrate the effectiveness of the obtained results.


2014 ◽  
Vol 687-691 ◽  
pp. 2458-2461
Author(s):  
Feng Ling Jia

This paper investigates the projective synchronization of drive-response complex dynamical networks. Based on the stability theory for fractional-order differential equations, controllers are designed torealize the projective synchronization for complex dynamical networks. Morover, some simple synchronization conditions are proposed. Numerical simulations are presented to show the effectiveness of the proposed method.


2013 ◽  
Vol 2013 ◽  
pp. 1-8
Author(s):  
Xuefei Wu ◽  
Chen Xu

This paper investigates the mean-square exponential synchronization issues of delayed stochastic complex dynamical networks with switching topology and impulsive control. By using the Lyapunov functional method, impulsive control theory, and linear matrix inequality (LMI) approaches, some sufficient conditions are derived to guarantee the mean-square exponential synchronization of delay complex dynamical network with switch topology, which are independent of the network size and switch topology. Numerical simulations are given to illustrate the effectiveness of the obtained results in the end.


2015 ◽  
Vol 2015 ◽  
pp. 1-6
Author(s):  
Luo Yi-ping ◽  
Luo Xin ◽  
Deng Fei ◽  
Hu Jun-qiang

This paper discusses the stability and synchronization for the nonlinear coupled complex networks with different dimensional nodes, and the external coupling satisfies the condition of dissipation. The definition of synchronization of the complex dynamical networks is proposed as the manifold. By Lyapunov stability theorem, the decentralized controllers with similar parameters are designed to synchronize such dynamical networks asymptotically in which the characteristics are variable delayed. Finally, a numerical example is given to illustrate the effectiveness of the designed method.


2014 ◽  
Vol 926-930 ◽  
pp. 1939-1942 ◽  
Author(s):  
Feng Ling Jia

In this paper, the function projective synchronization of complex dynamical networks is investigated. Based on the stability theory for fractional-order differential equations, an effective control scheme is proposed to achieve function projective synchronization for complex dynamical networks. Corresponding numerical simulations are presented to show the effectiveness of the proposed synchronization criteria.


Author(s):  
Ping He

Abstract In this paper, generalized outer synchronization between two different stochastic coupled complex dynamical networks with time-varying delays has been investigated. A novel controller is given and the stochastic invariance principle is applied. A stochastic disturbance which is described in term of a Brownian motion are considered in complex dynamical networks. Moreover, some sufficient conditions are derived to ensure generalized outer synchronization of stochastic neural networks. Surprisingly, it is found that complex networks with different structure can be synchronized.


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