Observer-based sliding mode control for synchronization of delayed chaotic neural networks with unknown disturbance

被引：50

作者：

Zhao, Yongshun ^{[1
]}

Li, Xiaodi ^{[1
,2
]}

Duan, Peiyong ^{[2
,3
]}

机构：

[1] Shandong Normal Univ, Sch Math & Stat, Jinan 250014, Shandong, Peoples R China

[2] Shandong Normal Univ, Sch Math & Stat, Shandong Key Lab Med Phys & Image Proc, Jinan 250014, Shandong, Peoples R China

[3] Shandong Normal Univ, Sch Informat Sci & Engn, Jinan 250014, Shandong, Peoples R China

来源：

NEURAL NETWORKS | 2019年 / 117卷

基金：

中国国家自然科学基金;

关键词：

Chaotic neural networks; Sliding mode control; Lyapunov-Krasovskii functional; Linear matrix inequality (LMI); Disturbance observer; TIME-VARYING DELAYS; MIXED DELAYS; STABILITY; SYSTEMS; DESIGN;

D O I：

10.1016/j.neunet.2019.05.013

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper considers the synchronization of delayed chaotic neural networks with unknown disturbance via observer-based sliding mode control. We design a sliding surface involving integral structure and a discontinuous control law such that the trajectories of error system converge to the sliding surface in finite time and remain on it thereafter. Then, by constructing Lyapunov-Krasovskii functional and using the linear matrix inequality (LMI) technique, some sufficient conditions are derived to guarantee the synchronization of chaotic neural networks. The advantages of our proposed results include:(i) It can be applied to synchronous control for drive and response systems with different structures; (ii) It can be applied to the response system with unknown disturbance. Finally, a simulation example is shown to illustrate the proposed methods. (C) 2019 Elsevier Ltd. All rights reserved.

引用

页码：268 / 273

页数：6

共 34 条

[1]

Ali MS, 2017, ACTA MATH SCI, V37, P368

[2] A modified Lyapunov functional with application to stability of neutral-type neural networks with time delays [J].

Arik, Sabri .

JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2019, 356 (01) :276-291

[3] An improved robust stability result for uncertain neural networks with multiple time delays [J].

Arik, Sabri .

NEURAL NETWORKS, 2014, 54 :1-10

[4] Sliding mode predictive control of linear uncertain systems with delays [J].

Caballero-Barragan, Humberto ;

Patricia Osuna-Ibarra, Linda ;

Loukianov, Alexander G. ;

Plestan, Franck .

AUTOMATICA, 2018, 94 :409-415

[5] Sliding mode synchronization of multiple chaotic systems with uncertainties and disturbances [J].

Chen, Xiangyong ;

Park, Ju H. ;

Cao, Jinde ;

Qiu, Jianlong .

APPLIED MATHEMATICS AND COMPUTATION, 2017, 308 :161-173

[6] Synchronization of memristive neural networks with mixed delays via quantized intermittent control [J].

Feng, Yuming ;

Yang, Xinsong ;

Song, Qiang ;

Cao, Jinde .

APPLIED MATHEMATICS AND COMPUTATION, 2018, 339 :874-887

[7] Robust H∞ Control for Stochastic T-S Fuzzy Systems via Integral Sliding-Mode Approach [J].

Gao, Qing ;

Feng, Gang ;

Liu, Lu ;

Qiu, Jianbin ;

Wang, Yong .

IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2014, 22 (04) :870-881

[8] Pinning-controlled synchronization of delayed neural networks with distributed-delay coupling via impulsive control [J].

He, Wangli ;

Qian, Feng ;

Cao, Jinde .

NEURAL NETWORKS, 2017, 85 :1-9

[9] Generalized synchronization for delayed chaotic neural networks: a novel coupling scheme [J].

Huang, Xia ;

Cao, Jinde .

NONLINEARITY, 2006, 19 (12) :2797-2811

[10] Finite-time lag synchronization of time-varying delayed complex networks via periodically intermittent control and sliding mode control [J].

Jing, Taiyan ;

Chen, Fangqi ;

Zhang, Xiaohua .

NEUROCOMPUTING, 2016, 199 :178-184

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