Finite-time synchronization control of a class of fractional-order complex network systems

2016 ◽  
Vol 33 (1) ◽  
pp. 96
Author(s):  
Beixing Mao ◽  
Zhanwei Wang
Keyword(s):  
Complex Network ◽  
Fractional Order ◽  
Finite Time ◽  
Time Synchronization ◽  
Synchronization Control ◽  
Order Complex ◽  
Network Systems

scholarly journals Adaptive Pinning Synchronization Control of the Fractional-Order Chaos Nodes in Complex Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-7
Author(s):  
Darui Zhu ◽  
Ling Liu ◽  
Chongxin Liu
Keyword(s):  
Complex Network ◽  
Fractional Order ◽  
Design Methodology ◽  
Small World ◽  
Synchronization Control ◽  
Order Complex ◽  
Small World Network ◽  
Network Systems ◽  
Control Scheme ◽  
Synchronization Performance

Adaptive pinning synchronization control is studied for a class of fractional-order complex network systems which are constructed depending on small-world network algorithm. Based on the fractional-order stability theory, the suitable adaptive control scheme is designed to guarantee global asymptotic stability of all the nodes in complex network systems and the node selected algorithm is given. In numerical implementation, it is shown that the numerical solution of the fractional-order complex network systems can be obtained by applying an improved version of Adams-Bashforth-Moulton algorithm. Furthermore, simulation results are provided to confirm the validity and synchronization performance of the advocated design methodology.

Finite-time synchronization of fractional-order complex networks via hybrid feedback control

2018 ◽  
Vol 320 ◽  
pp. 69-75 ◽  
Author(s):  
Hong-Li Li ◽  
Jinde Cao ◽  
Haijun Jiang ◽  
Ahmed Alsaedi
Keyword(s):  
Feedback Control ◽  
Complex Networks ◽  
Fractional Order ◽  
Finite Time ◽  
Time Synchronization ◽  
Order Complex

Projective synchronization via adaptive pinning control for fractional-order complex network with time-varying coupling strength

2019 ◽  
Vol 30 (07) ◽  
pp. 1940013
Author(s):  
Darui Zhu ◽  
Rui Wang ◽  
Chongxin Liu ◽  
Jiandong Duan
Keyword(s):  
Complex Network ◽  
Fractional Order ◽  
Control Method ◽  
Pinning Control ◽  
Projective Synchronization ◽  
Synchronization Control ◽  
Order Complex ◽  
Selection Algorithm ◽  
Feedback Control Method ◽  
Simulation Results

This paper presents an adaptive projective pinning control method for fractional-order complex network. First, based on theories of complex network and fractional calculus, some preliminaries of mathematics are given. Then, an analysis is conducted on the adaptive projective pinning control theory for fractional-order complex network. Based on the projective synchronization control method and the combined adaptive pinning feedback control method, suitable projection synchronization scale factor, adaptive feedback controller and the node selection algorithm are designed to illustrate the synchronization for fractional-order hyperchaotic complex network. Simulation results show that all nodes are stabilized to equilibrium point. Theoretical analysis and simulation results demonstrate that the designed adaptive projective pinning controllers are efficient.

Finite-time Synchronization of fractional-order complex-valued fuzzy cellular neural networks with time-varying delays

2021 ◽  
pp. 1-11
Author(s):  
Wenbin Jin ◽  
Wenxia Cui ◽  
Zhenjie Wang
Keyword(s):  
Neural Networks ◽  
Fractional Order ◽  
Finite Time ◽  
Time Synchronization ◽  
Sufficient Conditions ◽  
Cellular Neural Networks ◽  
Time Varying ◽  
Order Complex ◽  
Fuzzy Cellular Neural Networks ◽  
Complex Valued

Finite-time synchronization is concerned for the fractional-order complex-valued fuzzy cellular neural networks (FOCVFCNNs) with leakage delay and time-varying delays. Without using the usual complex-valued system decomposition method, this paper designs the different forms of the controllers by using 2-norm. And we construct the appropriate Lyapunov functional and apply inequality analytical techniques, some new sufficient conditions are obtained to ensure finite-time synchronization of the FOCVFCNNs. The upper bound of setting-time function is obtained. Finally, numerical examples are examined to illustrate the effectiveness of the analytical results.

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