Advanced sampled-data synchronization control for complex dynamical networks with coupling time-varying delays

Lee, Seung-Hoon; Park, Myeongjin; Kwon, Oh-Sang; Sakthivel, R.

doi:10.1016/j.ins.2017.08.071

Cited by 51 publications

(22 citation statements)

References 38 publications

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“…Remark 4. The controllers (10) and (19) indicate that all nodes in the network need target node information, and although many synchronization methods are such as [5][6][7], this is a limitation to the proposed method. This is because in large networks, depending on the network structure, all nodes may not have access to the target node.…”

Section: Control Design For Complex Dynamical Network With Dynamic LImentioning

confidence: 99%

“…One of these issues is the switching problem of coupling connection between nodes, which assumes that the network topology can vary over time (scheduled or stochastically) [18][19][20]. The problem of delayed couplings, with its strong analytical background and its definitive existence in many real systems due to the limited speed of data transmission, has been extensively studied [5,21,22]. Xu [24].…”

Section: Introductionmentioning

confidence: 99%

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Synchronization of Complex Dynamical Networks with Dynamical Behavior Links

Kazemy

Shojaei

2018

Asian Journal of Control

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In this paper, synchronization of a complex dynamical network (CDN) is investigated while the coupling connections of the network exhibit dynamic behavior. As it is shown in simulations, the dynamic links can cause synchronization losing in the network whereas the links in many real-world CDNs have dynamic behavior. To analyzing the effect of these links, two different CDN models are considered: without time delays and with delays in the coupling connections. By means of Lyapunov(-Krasovskii) theory, stability analysis of the error dynamics between the nodes of these CDNs and an introduced individual node is investigated which yields some conditions in the form of linear matrix inequalities (LMIs). These LMIs can be solved easily by various existing LMI solvers. Moreover, the gain matrices of state feedback controllers will be obtained by solving the LMIs. In the end, illustrative numerical examples are given to specify the effectiveness of the proposed method.

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Section: Control Design For Complex Dynamical Network With Dynamic LImentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Synchronization of Complex Dynamical Networks with Dynamical Behavior Links

Kazemy

Shojaei

2018

Asian Journal of Control

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“…In 2010, Li et al first explored the stability of CSNs by means of the Lyapunov method and graph‐theoretical technique. After that, based on the work of Li and Shuai, many interesting results were reported for more general CSNs, such as the stability of stochastic CSNs, the stability of complex‐valued CSNs, and the synchronization of CSNs . However, it should be pointed out that the aforementioned works only consider CSNs with single coupling.…”

Section: Introductionmentioning

confidence: 99%

“…After that, based on the work of Li and Shuai, 5 many interesting results were reported for more general CSNs, such as the stability of stochastic CSNs, 6-9 2364 2365 the stability of complex-valued CSNs, 10,11 and the synchronization of CSNs. [12][13][14][15][16] However, it should be pointed out that the aforementioned works only consider CSNs with single coupling. This kind of CSNs will restrict the study of many real-world applications.…”

mentioning

confidence: 99%

Stability of impulsive coupled systems on networks with both multicoupling structure and time‐varying delays

Wang

Sun

Fan

et al. 2019

Intl J Robust & Nonlinear

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Summary This paper explores the stability of impulsive coupled systems on networks with both multicoupling structure and time‐varying delays (ICSNMT). The coupling structure can be nonlinear and the time‐varying delays in which can be different, which can well describe more realistic networks. In order to describe this multicoupling structure, we build ICSNMT on a digraph with multiple arcs. Two cases are discussed, ie, (i) the continuous dynamics is stable and (ii) the impulsive dynamics is stable. Then, by means of impulsive differential inequalities with multiple delays and weighted Lyapunov functions method where the weights are closely linked to the network's topological structure, some stability criteria are established. Then, the theoretical results are illustrated by examples of bidirectional associative memory neural networks and coupled modified Chua's circuits, respectively. The numerical simulations are also carried out to demonstrate the effectiveness and feasibility of our theoretical findings.

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“…In Yang, Cao, and Lu (2012), the authors studied synchronization of complex networks with the hybrid adaptive and impulsive control methods. With recent advancement in digital measurement, high quality computers, communication networks and intelligent instruments, continuous-time controllers are been replaced with digital controllers (Lee, Park, Kwon, & Sakthivel, 2017). Furthermore, these have resulted in improved reliability, accuracy and better stability performance.…”

Section: Introductionmentioning

confidence: 99%

Exponential H_∞ synchronization of non-fragile sampled-data controlled complex dynamical networks with random coupling and time varying delay

Adu-Gyamfi

Cheng

Yin

et al. 2018

Systems Science & Control Engineering

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This paper investigates the problem of non-fragile sampled-data control for synchronization of complex dynamical networks with randomly coupling and time varying delay under exponential H ∞ approach. By adopting an appropriate Lyapunov Krasovskii functional (LKF) and taking into consideration full information on the sampling pattern, free-matrix based integral and Wirtinger inequalities are explored leading to the establishment of sufficient conditions to guarantee the exponential H ∞ synchronization stability and disturbance attenuation of the closed loop network, with a designed non-fragile controller under all randomly admissible gain variations. The results are presented in terms of Linear matrix inequalities (LMIs), which can effectively be solved by some available softwares. Finally, two simulated results are demonstrated to show the effectiveness and less conservativeness of our proposed scheme. ARTICLE HISTORY

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Advanced sampled-data synchronization control for complex dynamical networks with coupling time-varying delays

Cited by 51 publications

References 38 publications

Synchronization of Complex Dynamical Networks with Dynamical Behavior Links

Synchronization of Complex Dynamical Networks with Dynamical Behavior Links

Stability of impulsive coupled systems on networks with both multicoupling structure and time‐varying delays

Exponential H_∞ synchronization of non-fragile sampled-data controlled complex dynamical networks with random coupling and time varying delay

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Advanced sampled-data synchronization control for complex dynamical networks with coupling time-varying delays

Cited by 51 publications

References 38 publications

Synchronization of Complex Dynamical Networks with Dynamical Behavior Links

Synchronization of Complex Dynamical Networks with Dynamical Behavior Links

Stability of impulsive coupled systems on networks with both multicoupling structure and time‐varying delays

Exponential H∞ synchronization of non-fragile sampled-data controlled complex dynamical networks with random coupling and time varying delay

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Product

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Exponential H_∞ synchronization of non-fragile sampled-data controlled complex dynamical networks with random coupling and time varying delay