Synchronization of a Class of Switched Neural Networks with Time-Varying Delays via Nonlinear Feedback Control

Wang, Leimin; Zhang, Guodong

doi:10.1109/tcyb.2015.2475277

Cited by 94 publications

(45 citation statements)

References 55 publications

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“…Furthermore, the synchronization play an extremely important role in many fields of science including biology, climatology, sociology, ecology [13][14][15][16][17][18][19][20][21] . In view of the significance of the synchronization for delayed recurrent cellular neural networks (RCNNs), there are many important works have been developed to stabilize or synchronize neural networks and nonlinear systems [13][14][15][16][17][18][19][20][21][22][23][24] .…”

Section: Introductionmentioning

confidence: 99%

Synchronization stability for recurrent neural networks with time-varying delays

Muhammadhaji¹,

Halik²

2019

ScienceAsia

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This paper studies the general decay synchronization (GDS) of a class of recurrent neural networks (RNNs) with general activation functions and time-varying delays. By constructing suitable Lyapunov-Krasovskii functionals and employing useful inequality techniques, some sufficient conditions on the GDS of considered RNNs are established via a type of nonlinear control. In addition, an example with numerical simulations is presented to illustrate the obtained theoretical results.

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Section: Introductionmentioning

confidence: 99%

Synchronization stability for recurrent neural networks with time-varying delays

Muhammadhaji¹,

Halik²

2019

ScienceAsia

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“…Then, we get the following solutions of (13), (33), and (34), and feedback gain matrix K as Letting (t) = e −2.8t and (t) = e t , then the hypothesis H 3 hold true. Therefore, according to Theorem 1, the master-slave systems (38) and (39) can be achieved GDS under controller (12). The time evolution of synchronization errors between master-slave systems (38) and (39) are shown in Figures 7, 8, and 9, where the initial values of slave Remark 8.…”

Section: Examplementioning

confidence: 92%

“…Remark For the synchronization conditions given in other works, the time delays assumed to be constant delays or time‐varying delays that are differentiable such that their derivatives are not greater than one. Note that, in our assumption H 1 , those restrictions are removed in this paper, which means that our established results have a wider applicability.…”

Section: Numerical Simulationsmentioning

confidence: 99%

“…The time evolution of synchronization errors between master-slave systems (38) and (39) are shown in Figures 7, 8, and 9, where the initial values of slave Remark 8. For the synchronization conditions given in other works, 2,23,24,[27][28][29][30]39 the time delays assumed to be constant delays or time-varying delays that are differentiable such that their derivatives are not greater than one. Note that, in our assumption H 1 , those restrictions are removed in this paper, which means that our established results have a wider applicability.…”

Section: Examplementioning

confidence: 99%

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Nonlinear output control scheme for general decay synchronization of delayed neural networks with inertial term

Abdurahman

Jiang

Sader

2019

Intl J Robust & Nonlinear

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Summary This study is mainly concerned with the general decay synchronization (GDS) problem of a class of inertial neural networks (INNs) with time‐varying delay. First, unlike the methods used in previous relevant literature where both of the master and slave systems were transferred into the first‐order differential equations, only error dynamical system is transferred into the reduced‐order differential equation. Then, by designing a novel nonlinear output feedback controller and constructing suitable Lyapunov functionals, some simple and useful sufficient conditions ensuring the GDS of considered INNs are established via employing useful analysis techniques and linear matrix inequality approach. In addition, two examples are presented to show the effectiveness of the established theoretical results.

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“…Consensus of MASs with time delays has been extensively studied in existing literatures, e.g. [24,79,80,81,132,133,82,134,135]. Most of the existing works have focused on agents of simple dynamics, e.g.…”

Section: Introductionmentioning

confidence: 99%

Distributed Consensus of Linear Multiagent Systems: Laplacian Spectra-Based Method

Chen

Shi

2020

IEEE Trans. Syst. Man Cybern, Syst.

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With the help of rapidly advancing communication technology, control systems are increasingly integrated via communication networks. Networked control systems (NCSs) bring significant advantages such as flexible and scalable structures, easy implementation and maintenance, and efficient resources distribution and allocation. NCSs empowers to finish some complicated tasks using some relatively simple systems in a collaborated manner. However, there are also some challenges and constraints subject to the imperfection of communication channels. In this thesis, the stabilization problems and the performance limitation problems of control systems subject to networked-induced constraints are studied. Overall, the thesis mainly includes two parts: 1) Consensus and consensusability of multi-agent systems (MASs); 2) Delay margins of NCSs. Chapter 2 and Chapter 3 deal with the consensus problems of MASs, which aim to properly design the control protocols to ensure the state convergence of all the agents. Chapter 4 and Chapter 5 focus on the consensusability analysis, exploring how the dynamics of the agents and the networked induced constraints impact the overall systems for achieving consensus. Chapter 6 pays attention to the delay margins of discrete-time linear time-invariant (LTI) systems, studying how the dynamics of the plants limit the time delays that can be tolerated by LTI controllers. on the discrete-time delay margin led to negative results, the bounds developed in this chapter provide instead a guaranteed range of delays within which the delayed plants can be robustly stabilized, and in turn solve the special class of simultaneous stabilization problems in question. Finally, in Chapter 7, the thesis is summarized and some future research topics are also presented.

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Synchronization of a Class of Switched Neural Networks with Time-Varying Delays via Nonlinear Feedback Control

Cited by 94 publications

References 55 publications

Synchronization stability for recurrent neural networks with time-varying delays

Synchronization stability for recurrent neural networks with time-varying delays

Nonlinear output control scheme for general decay synchronization of delayed neural networks with inertial term

Distributed Consensus of Linear Multiagent Systems: Laplacian Spectra-Based Method

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