Exponential synchronization of Markovian jumping chaotic neural networks with sampled-data and saturating actuators

Rakkiyappan, R.; Latha, V. Preethi; Zhu, Quanxin; Yao, Zhangsong

doi:10.1016/j.nahs.2016.10.004

Cited by 84 publications

(28 citation statements)

References 40 publications

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“…Input saturation problem in nonlinear dynamical systems has been recognized as a difficult work. In order to better handle saturated nonlinear models, there are two approaches in current works . The first approach is based on polytopic differential inclusion, which involves a local description of the saturated system via a polytopic representations .…”

Section: Introductionmentioning

confidence: 99%

Exponential stabilization for nonlinear coupled dynamical systems via impulsive and sampled‐data control with input constraints

Zhang

et al. 2019

Intl J Robust & Nonlinear

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Summary In this paper, exponential stabilization for nonlinear coupled dynamical systems by considering sampled‐data controller and impulsive controller with input constraints is investigated. Based on polytopic representation approach, some linear matrix inequalities are established to guarantee local exponential stabilization of nonlinear coupled dynamical systems. Moreover, by using polytopic differential inclusion, for the case of the partial input saturation involving in the impulsive controller, we also obtain several sufficient conditions ensuring local exponential stabilization. Finally, three examples are presented to show the effectiveness of theoretical analysis.

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Section: Introductionmentioning

confidence: 99%

Exponential stabilization for nonlinear coupled dynamical systems via impulsive and sampled‐data control with input constraints

Zhang

et al. 2019

Intl J Robust & Nonlinear

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“…One of the major topics drawing considerable concerns is synchronization of CNs. Currently, many results on synchronization analysis of CNs have been achieved for the strong demands from diverse sorts of fields in parallel image processing, pattern recognition, and secure communication . Besides, fractional‐order calculus can be seen as a generalization of integer‐order differentiation and integration to arbitrary non‐integer order.…”

Section: Introductionmentioning

confidence: 99%

Synchronization for fractional‐order multi‐linked complex network with two kinds of topological structure via periodically intermittent control

2019

Math Methods in App Sciences

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This paper concentrates on the global synchronization of the fractional‐order multi‐linked complex network (FMCN) via periodically intermittent control. It should be stressed that periodically intermittent control is employed to the FMCN for the first time. Moreover, the network is defined on digraphs with different weights, and two situations on topological structure of the network are discussed, including each digraph being strongly connected, and the biggest one being strongly connected. Based on Lyapunov method and graph theory, some synchronization criteria are obtained under two situations. And, the obtained synchronization criteria have a close relationship with the order of fractional‐order derivative, coupling strength, control gain, control rate, and control period. Besides, for practicability, theoretical results are applied to studying the synchronization of fractional‐order multi‐linked chaotic systems, and some sufficient conditions are provided. For a special case, fractional‐order multi‐linked Lorenz chaotic systems, numerical simulations are given to indicate the feasibility of theoretical results and the effectiveness of control strategy.

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“…Then, various effective control approaches and techniques have been proposed for synchronization, such as impulsive control, feedback control, adaptive control, and intermittent control (see [21,22]). And a lot of achievements have been 2 Discrete Dynamics in Nature and Society made in the stability and synchronization problem of MNNs, including exponential synchronization, lag synchronization, and finite time synchronization (see [23][24][25][26]). …”

Section: Introductionmentioning

confidence: 99%

Analysis of Adaptive Synchronization for Stochastic Neutral-Type Memristive Neural Networks with Mixed Time-Varying Delays

Hong

Zhang

Yang

2018

Discrete Dynamics in Nature and Society

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Linear feedback control and adaptive feedback control are proposed to achieve the synchronization of stochastic neutral-type memristive neural networks with mixed time-varying delays. By applying the stochastic differential inclusions theory, Lyapunov functional, and linear matrix inequalities method, we obtain some new adaptive synchronization criteria. A numerical example is given to illustrate the effectiveness of our results.

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Exponential synchronization of Markovian jumping chaotic neural networks with sampled-data and saturating actuators

Cited by 84 publications

References 40 publications

Exponential stabilization for nonlinear coupled dynamical systems via impulsive and sampled‐data control with input constraints

Exponential stabilization for nonlinear coupled dynamical systems via impulsive and sampled‐data control with input constraints

Synchronization for fractional‐order multi‐linked complex network with two kinds of topological structure via periodically intermittent control

Analysis of Adaptive Synchronization for Stochastic Neutral-Type Memristive Neural Networks with Mixed Time-Varying Delays

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