Adaptive Semi-Periodically Intermittent and Lag Synchronization Control of Neural Networks With Mixed Delays

Li, Ning; Sun, Hao; Li, Zhoutong; Zhang, Qingling

doi:10.1109/access.2017.2787572

Cited by 14 publications

(3 citation statements)

References 31 publications

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“…where x ( t ) = [ x 1 ( t ) , x 2 ( t ) ,… , x n ( t ) ] T , x i ( t ) denotes the state of the i th neuron, f ( x ( t ) ) represents the neuron activation function satisfying 34…”

Section: Preliminaries and Problem Formulationmentioning

confidence: 99%

Reliable mode-dependent memorized projective lag synchronization for semi-Markovian jumping coupled networks

2021

Proceedings of the Institution of Mechanical Engineers, Part I:

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This article investigates the reliable projective lag synchronization problem for semi-Markovian jumping coupled networks under the master–slave framework. More precisely, a novel mode-dependent memorized synchronization scheme is proposed for the master and slave dynamical networks. By utilizing the Lyapunov-Krasovskii method, sufficient delay-dependent conditions are derived to achieve the reliable synchronization in the mean-square sense. Based on the derived results, the mode-dependent synchronization controller is further designed by convex optimization. In the end, two numerical examples are given to illustrate the effectiveness of the obtained theoretical results.

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“…where x ( t ) = [ x 1 ( t ) , x 2 ( t ) ,… , x n ( t ) ] T , x i ( t ) denotes the state of the i th neuron, f ( x ( t ) ) represents the neuron activation function satisfying 34…”

Section: Preliminaries and Problem Formulationmentioning

confidence: 99%

Reliable mode-dependent memorized projective lag synchronization for semi-Markovian jumping coupled networks

2021

Proceedings of the Institution of Mechanical Engineers, Part I:

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“…The research on synchronization control of complex networks is helpful to understand the influence of network structure on synchronization of complex systems, which can supplement the synchronization analysis of complex networks. [20][21][22] In the study of synchronous control of complex networks, many control methods have been introduced, such as adaptive control, [22,23] pinning control, [24,25] intermittent control, [26,27] finite-time control, [27][28][29][30][31] and sampled-data control. [32] The collaborative scheduling control of the transportation network can be taken as an example of the CPS system.…”

Section: Introductionmentioning

confidence: 99%

Dynamic modeling and aperiodically intermittent strategy for adaptive finite-time synchronization control of the multi-weighted complex transportation networks with multiple delays*

Li¹,

Sun²,

Xin³

et al. 2021

Chinese Phys. B

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The idea of network splitting according to time delay and weight is introduced. Based on the cyber physical systems (CPS), a class of multi-weighted complex transportation networks with multiple delays is modeled. The finite-time synchronization of the proposed complex transportation networks model is studied systematically. On the basis of the theory of stability, the technique of adaptive control, aperiodically intermittent control and finite-time control, the aperiodically intermittent adaptive finite-time synchronization controller is designed. The controller designed in this paper is beneficial for understanding the synchronization in multi-weighted complex transportation networks with multiple delays. In addition, the conditions for the existence of finite time synchronization have been discussed in detail. And the specific value of the settling finite time for synchronization is obtained. Moreover, the outer coupling configuration matrices are not required to be irreducible or symmetric. Finally, simulation results of the finite-time synchronization problem are given to illustrate the correctness of the results obtained.

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“…This behavior has appeared in lasers, neural models, electronic applications, and secure communication [7,13], which can cause instability and poor performance. Therefore, lag synchronization has become a hot topic in the research of complex networks and many works have been presented [1,14,23,24,31].…”

Section: Introductionmentioning

confidence: 99%

Lag synchronization of uncertain complex dynamical networks with derivative coupling

Al-mahbashi¹,

Noorani²

2018

J. Nonlinear Sci. Appl.

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In this study, uncertain complex dynamical network model with time varying coupling delay and derivative coupling delay is considered. The lag synchronization between two such uncertain networks with different nodes is investigated. An adaptive control method is designed by using Lyapunov stability theory for achieving the lag synchronization and some corollaries are also given. In addition, on the basis of the adaptive update law, unknown parameters of the networks are estimated. The analytical results show that the states of the dynamical network with derivative delay coupling can be asymptotically synchronized under the designed control. The numerical simulation results also demonstrate the validity of the designed method.

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Adaptive Semi-Periodically Intermittent and Lag Synchronization Control of Neural Networks With Mixed Delays

Cited by 14 publications

References 31 publications

Reliable mode-dependent memorized projective lag synchronization for semi-Markovian jumping coupled networks

Reliable mode-dependent memorized projective lag synchronization for semi-Markovian jumping coupled networks

Dynamic modeling and aperiodically intermittent strategy for adaptive finite-time synchronization control of the multi-weighted complex transportation networks with multiple delays*

Lag synchronization of uncertain complex dynamical networks with derivative coupling

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