Further results on event-triggered H∞ networked control for neural networks with stochastic cyber-attacks

被引：16

作者：

Feng, Zongying ^{[1
]}

Shao, Hanyong ^{[1
]}

Shao, Lin ^{[2
]}

机构：

[1] Qufu Normal Univ, Inst Automat, Rizhao 276826, Peoples R China

[2] Shandong Univ Sci & Technol, Coll Elect & Informat Engn, Qingdao 266590, Peoples R China

来源：

APPLIED MATHEMATICS AND COMPUTATION | 2020年 / 386卷 / 386期

基金：

中国国家自然科学基金;

关键词：

Event-triggered scheme; Neural networks; Mean-square stable; Stochastic cyber-attacks; H-infinity Performance; DELAY-DEPENDENT STABILITY; LARGE-SCALE SYSTEMS; COMMUNICATION SCHEME; SYNCHRONIZATION; STABILIZATION; CRITERIA;

D O I：

10.1016/j.amc.2020.125431

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

This paper is concerned with decentralized event-triggered H-infinity networked control for neural networks (NNs) subject to two types of stochastic cyber-attacks. Firstly, a new dynamic event-triggered scheme is introduced to monitor the sampled data transmissions, and two independent Bernoulli distributed variables are used to describe the randomly occurring cyber-attacks. Secondly, based on the networked control, the closed-loop system is constructed under the stochastic cyber-attacks and limited network bandwidth. Thirdly, by the Lyapunov-Krasovskii functional (LKF) approach, an improved stability criterion is established to ensure the closed-loop system is mean-square asymptotical stability with a prescribed H-infinity performance. Based on the criterion, desired control gain is determined. Finally, the effectiveness of the obtained result is illustrated by two numerical examples. (C) 2020 Elsevier Inc. All rights reserved.

引用

页数：20

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