Extended dissipativity stabilization and synchronization of uncertain stochastic reaction-diffusion neural networks via intermittent non-fragile control

被引：35
作者：
Ding, Kui [1 ,2 ,3 ]
Zhu, Quanxin [1 ,3 ]
Liu, Lijun [4 ]
机构：
[1] Hunan Normal Univ, Sch Math & Stat, MOE LCSM, Changsha 410081, Hunan, Peoples R China
[2] Qingdao Univ Sci & Technol, Sch Math & Phys, Qingdao, Shandong, Peoples R China
[3] Nanjing Normal Univ, Sch Math Sci, Nanjing 210023, Jiangsu, Peoples R China
[4] Nanjing Univ Aeronaut & Astronaut, Coll Automat Engn, Nanjing 210016, Jiangsu, Peoples R China
来源：
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS | 2019年 / 356卷 / 18期
基金：
中国国家自然科学基金;
关键词：
H-INFINITY SYNCHRONIZATION; TIME-VARYING DELAYS; SYSTEMS; DISCRETE; PASSIVITY; STABILITY; SUBJECT;
D O I：
10.1016/j.jfranklin.2019.09.047
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper mainly studies the problem of extended dissipativity stabilization and synchronization of a class of uncertain stochastic reaction-diffusion neural networks with discrete and distributed time-varying delays via intermittent non-fragile control strategies. A novel stabilization and synchronization criteria and extended dissipative analysis is obtained by combining a switching time dependent Lyapunov functional method with Wirtinger's inequality technique. Then, by solving a set of delay dependent linear matrix inequalities, we obtain the desired intermittent non-fragile controller, which can be used to satisfies the prescribed level of extended dissipativity behaviors, including H-infinity behavior, passivity action, (Q, S, R)-dissipative performance, and L-2 - L-infinity performance. Finally, two numerical examples are adopted to verify the validity of the stabilization and synchronization results. (C) 2019 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码：11690 / 11715
页数：26
相关论文
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