scholarly journals Exponential synchronization of a complex dynamical network with piecewise-homogeneous Markovian jump structure and coupling delay

2019 ◽  
Author(s):  
Nasim Akbari ◽  
Ali Sadr ◽  
Ali Kazemy ◽  
Mona Faraji-Niri
Keyword(s):  
Exponential Synchronization ◽  
Complex Dynamical Network ◽  
Markovian Jump ◽  
Coupling Delay ◽  
Dynamical Network

scholarly journals Adaptive Aperiodically Intermittent Synchronization for Complex Dynamical Network with Unknown Time-Varying Outer Coupling Strengths

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Lihong Yan ◽  
Junmin Li
Keyword(s):  
Adaptive Learning ◽  
Exponential Synchronization ◽  
Intermittent Control ◽  
Time Varying ◽  
Complex Dynamical Network ◽  
Dynamical Network ◽  
Synchronization Problem ◽  
Coupling Strengths ◽  
Inequality Techniques ◽  
Theoretical Results

In this paper, exponential synchronization problem of complex dynamical networks with unknown periodically coupling strengths was investigated. An aperiodically intermittent control synchronization strategy is proposed. Based on Lyapunov exponential stability theory, inequality techniques, and adaptive learning laws design, some sufficient exponential synchronization criteria for complex dynamical network with unknown periodical coupling weights are obtained. The numerical simulation example is presented to illustrate the feasibility of theoretical results.

Robust exponential synchronization of a Markovian jump complex dynamical network with piecewise homogeneous Markovian parameters

2020 ◽  
Vol 37 (4) ◽  
pp. 1168-1191
Author(s):  
Nasim Akbari ◽  
Ali Sadr ◽  
Ali Kazemy
Keyword(s):  
System Dynamics ◽  
Linear Matrix ◽  
Uncertain Information ◽  
Time Varying ◽  
Complex Dynamical Network ◽  
Markovian Jump ◽  
Piecewise Constant ◽  
Dynamical Network ◽  
High Level ◽  
Bounded Uncertainties

Abstract This paper establishes a stochastic synchronization method for a Markovian jump complex dynamical network (MJCDN) with time-delay and uncertainties. The considered Markovian structure is piecewise-homogeneous with piecewise-constant time-varying transition rates (TRs). Two Markovian signals are utilized to construct the piecewise-homogeneous Markovian structure. A low-level Markovian signal with time-varying TRs governs the switching between the system dynamics while it is managed by a high-level Markovian signal. Due to the effect of imperfections induced by modeling errors in the system dynamics, some parametric norm-bounded uncertainties are considered. In addition, uncertain TR matrix is considered which means that inaccurate or uncertain information for each element of the TR matrix is allowable. This modelling makes the MJCDN to be more general and applicable than the existing ones. Synchronization conditions are obtained and reported in the form of linear matrix inequalities by the help of Lyapunov–Krasovskii theory, Wirtinger-based integral inequality approach and reciprocally convex technique. Finally, a numerical example is presented to verify the effectiveness of the proposed method.

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