Synchronization of stochastic complex networks with discrete-time and distributed coupling delayed via hybrid nonlinear and impulsive control

2018 ◽  
Vol 114 ◽  
pp. 381-393 ◽  
Author(s):  
Mengzhuo Luo ◽  
Xinzhi Liu ◽  
Shouming Zhong ◽  
Jun Cheng
Keyword(s):  
Complex Networks ◽  
Discrete Time ◽  
Impulsive Control ◽  
Stochastic Complex Networks

scholarly journals Mean Square Asymptotic Boundedness of Stochastic Complex Networks via Impulsive Control

2020 ◽  
pp. 10-21
Author(s):  
Xiaoyi Zhu ◽  
Danhua He
Keyword(s):  
Asymptotic Stability ◽  
Lyapunov Function ◽  
Complex Systems ◽  
Complex Networks ◽  
Impulsive Control ◽  
Stability Conditions ◽  
Mean Square ◽  
The Mean ◽  
Stochastic Complex Networks ◽  
Asymptotic Stability Conditions

In this paper, the mean square asymptotic boundedness of a class of stochastic complex systems with different dynamic nodes represented by Ito stochastic differential equations is studied.  By using the Lyapunov function and Ito formula, the mean square asymptotic boundedness and mean square asymptotic stability conditions of stochastic complex systems with different dynamic nodes are obtained.

scholarly journals Synchronization Analysis for Stochastic T-S Fuzzy Complex Networks with Markovian Jumping Parameters and Mixed Time-Varying Delays via Impulsive Control

2020 ◽  
Vol 2020 ◽  
pp. 1-27 ◽  
Author(s):  
M. Syed Ali ◽  
M. Usha ◽  
Quanxin Zhu ◽  
Saravanan Shanmugam
Keyword(s):  
Complex Networks ◽  
Impulsive Control ◽  
Fuzzy Model ◽  
Linear Matrix ◽  
Time Varying ◽  
Markovian Jumping Parameters ◽  
Markovian Jumping ◽  
Stochastic Complex Networks ◽  
Delay Dependent ◽  
Takagi Sugeno

In this paper, we propose and explore the synchronization examination for fuzzy stochastic complex networks’ Markovian jumping parameters portrayed by Takagi-Sugeno (T-S) fuzzy model with mixed time-varying coupling delays via impulsive control. The hybrid coupling includes time-varying discrete and distributed delays. Based on appropriate Lyapunov–Krasovskii functional (LKF) approach, Newton–Leibniz formula, and Jensen’s inequality, the stochastic examination systems and Kronecker product to create delay-dependent synchronization criteria that guarantee stochastically synchronous of the proposed T-S fuzzy stochastic complex networks with mixed time-varying delays. Adequate conditions for the synchronization criteria for the frameworks are established in terms of linear matrix inequalities (LMIs). At long last, numerical examples and simulations are given to demonstrate the correctness of the hypothetical outcomes.

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