Robust passivity analysis for uncertain neural networks with discrete and distributed time-varying delays

被引：24
作者：
Ge, Chao [1 ]
Park, Ju H. [2 ]
Hua, Changchun [3 ]
Shi, Caijuan [1 ]
机构：
[1] North China Univ Sci & Technol, Inst Informat Engn, Tangshan, Peoples R China
[2] Yeungnam Univ, Dept Elect Engn, Kyongsan, South Korea
[3] Yanshan Univ, Inst Elect Engn, Qinhuangdao, Hebei, Peoples R China
来源：
NEUROCOMPUTING | 2019年 / 364卷
基金：
新加坡国家研究基金会;
关键词：
Uncertain neural networks; Passivity analysis; Time-varying delays; Lyapunov-Krasovskii functional; SAMPLED-DATA SYSTEMS; CHAOTIC LURE SYSTEMS; DECOMPOSING APPROACH; STABILITY; SYNCHRONIZATION; CRITERIA;
D O I：
10.1016/j.neucom.2019.06.077
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, we address robust passivity analysis for a class of uncertain neural networks (NNs) with discrete and distributed time-varying delays. By selecting an improved Lyapunov-Krasovskii functional (LKF) with a novel delay-produce-type (DPT) term and combing free-matrix-based (FMB) integral inequality, some sufficient criteria are obtained to guarantee the passivity of uncertain NNs. Then, the maximal allowable upper bound (MAUB) of time-varying delay can be obtained by reciprocally convex combination (RCC) technique through solving a group of linear matrix inequalities (LMIs). Finally, numerical examples are considered to illustrate the benefit and superiority of the method proposed. (C) 2019 Elsevier B.V. All rights reserved.
引用
收藏
页码：330 / 337
页数：8
相关论文
共 43 条
[1]   Improved passivity analysis for neural networks with Markovian jumping parameters and interval time-varying delays [J].
Chen, Guoliang ;
Xia, Jianwei ;
Zhuang, Guangming .
NEUROCOMPUTING, 2015, 155 :253-260
[2]   Improved delay-dependent robust passivity criteria for uncertain neural networks with discrete and distributed delays [J].
Chen, Zhiwen ;
Wang, Xin ;
Zhong, Shouming ;
Yang, Jun .
CHAOS SOLITONS & FRACTALS, 2017, 103 :23-32
[3]   Quantized H∞ filtering for switched linear parameter-varying systems with sojourn probabilities and unreliable communication channels [J].
Cheng, Jun ;
Park, Ju H. ;
Cao, Jinde ;
Zhang, Dian .
INFORMATION SCIENCES, 2018, 466 :289-302
[4]   A Flexible Terminal Approach to Sampled-Data Exponentially Synchronization of Markovian Neural Networks With Time-Varying Delayed Signals [J].
Cheng, Jun ;
Park, Ju H. ;
Karimi, Hamid Reza ;
Shen, Hao .
IEEE TRANSACTIONS ON CYBERNETICS, 2018, 48 (08) :2232-2244
[5]   Second-Order Sliding-Mode Controller Design and Its Implementation for Buck Converters [J].
Ding, Shihong ;
Zheng, Wei Xing ;
Sun, Jinlin ;
Wang, Jiadian .
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2018, 14 (05) :1990-2000
[6]   Complete delay-decomposing approach to exponential stability for uncertain cellular neural networks with discrete and distributed time-varying delays [J].
Du, Yuanhua ;
Wen, Wu ;
Zhong, Shouming ;
Zhou, Nan .
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS, 2016, 14 (04) :1012-1020
[7]   Controller Design Based On Wavelet Neural Adaptive Proportional Plus Conventional Integral-Derivative For Bilateral Teleoperation Systems With Time-Varying Parameters [J].
Ganjefar, Soheil ;
Afshar, Mohammad ;
Sarajchi, Mohammad Hadi ;
Shao, Zhufeng .
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS, 2018, 16 (05) :2405-2420
[8]   Decentralized Output Feedback Adaptive NN Tracking Control for Time-Delay Stochastic Nonlinear Systems With Prescribed Performance [J].
Hua, Changchun ;
Zhang, Liuliu ;
Guan, Xinping .
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2015, 26 (11) :2749-2759
[9]   Synchronization of Chaotic Lur'e Systems With Time Delays Using Sampled-Data Control [J].
Hua, Changchun ;
Ge, Chao ;
Guan, Xinping .
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2015, 26 (06) :1214-1221
[10]   Robust state estimation for uncertain neural networks with time-varying delay [J].
Huang, He ;
Feng, Gang ;
Cao, Jinde .
IEEE TRANSACTIONS ON NEURAL NETWORKS, 2008, 19 (08) :1329-1339
12345