Pinning sampled-data control for synchronization of complex networks with probabilistic time-varying delays using quadratic convex approach

Rakkiyappan, R.; Sakthivel, N.

doi:10.1016/j.neucom.2015.04.010

Cited by 56 publications

(11 citation statements)

References 43 publications

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“…The state trajectory of the isolated node α(t)s(t) (43) and network x i (t) (1) Remark 6 The networks in both examples of our study and the ones in the literature [21,32,39] are different. In [21], the FPS of the network is achieved under pinning feedback controller design but the concerned network is still undirected.…”

Section: Figure 11mentioning

confidence: 96%

“…It renders the control more reliable and handy in real world problems. In [29], one studied dissipative sampled-data control of uncertain nonlinear systems with timevarying delays, and so on [30][31][32][33][34]. Meanwhile, pinning control has been introduced to deal with the problem of large number of controllers added to large size of neural network structure [35][36][37][38][39].…”

Section: Introductionmentioning

confidence: 99%

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Mixed $H_{\infty }/$passive exponential function projective synchronization of delayed neural networks with hybrid coupling based on pinning sampled-data control

et al. 2019

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This paper presents the problem of mixed H ∞ /passive exponential function projective synchronization of delayed neural networks with constant discrete and distributed delay couplings under pinning sampled-data control scheme. The aim of this work is to focus on designing of pinning sampled-data controller with an explicit expression by which the stable synchronization error system is achieved and a mixed H ∞ /passive performance level is also reached. Particularly, the control method is designed to determine a set of pinned nodes with fixed coupling matrices and strength values, and to select randomly pinning nodes. To handle the Lyapunov functional, we apply some new techniques and then derive some sufficient conditions for the desired controller existence. Furthermore, numerical examples are given to illustrate the effectiveness of the proposed theoretical results.

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Section: Figure 11mentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

Mixed $H_{\infty }/$passive exponential function projective synchronization of delayed neural networks with hybrid coupling based on pinning sampled-data control

et al. 2019

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“…However, the synchronization conditions have not appeared under the condition that randomness of controller gain fluctuation, nonfragile character, sampled‐data, uncertainty, and time‐delays are considered in the state‐feedback controller. Many control methods have appeared to achieve synchronization including state‐feedback control, 16 adaptive control, 17 pinning control, 18,19 sliding mode control, 20 intermittent control, 21 and so on. Fragility is the basic problem of performance degradation of the feedback control for CDNs due to the phenomenon of inaccuracies in the process of implementing controller.…”

Section: Introductionmentioning

confidence: 99%

Novel results on nonfragile sampled‐data exponential synchronization for delayed complex dynamical networks

Zhao

Zhong

Zhang

et al. 2020

Intl J Robust & Nonlinear

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This article investigates exponential synchronization for complex dynamical networks (CDNs) with nonfragile sampled-data feedback control. An important yet challenging problem that contains the time delays of the controller, the uncertainties occurrence and randomness of controller gain fluctuation due to the packet loss, and time delays during data transmission is to be solved. A novel Lyapunov-Krasovskii functional (LKF) that allows for more free matrix terms and slacks certain one of the terms to nonpositive definite is first constructed based upon special refined block matrices. By employing the novel LKF and functional analysis theory, the nonfragile sampled-data feedback controller is developed to guarantee the exponential synchronization of CDNs and make a more optimal bound estimation of the sampled period. Finally, compared simulation examples are performed as significant to demonstrate the effective performance and the superiority of the proposed methods.

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“…The analog signal treatment methods have been frequently replaced by digital signal handling methods to afford better stability in continuous-time systems. Thus, sampled-data systems have been a hot research topic and investigated extensively in the last decades [27][28][29][30][31][32][33][34][35]. In such systems, a digital computer is adopted to sample and quantize a continuous-time measurement signal to produce a discrete-time signal, and then produce a discrete-time control input signal, which is further converted back into a continuous-time control input signal using a zero-order hold (ZOH) [36].…”

Section: Introductionmentioning

confidence: 99%

New result on synchronization of complex dynamical networks with time-varying coupling delay and sampled-data control

et al. 2016

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Pinning sampled-data control for synchronization of complex networks with probabilistic time-varying delays using quadratic convex approach

Cited by 56 publications

References 43 publications

Mixed $H_{\infty }/$passive exponential function projective synchronization of delayed neural networks with hybrid coupling based on pinning sampled-data control

Mixed $H_{\infty }/$passive exponential function projective synchronization of delayed neural networks with hybrid coupling based on pinning sampled-data control

Novel results on nonfragile sampled‐data exponential synchronization for delayed complex dynamical networks

New result on synchronization of complex dynamical networks with time-varying coupling delay and sampled-data control

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