Passivity-based control for Hopfield neural networks using convex representation

被引:56
|
作者
Ji, D. H. [2 ]
Koo, J. H. [3 ]
Won, S. C. [3 ]
Lee, S. M. [4 ]
Park, Ju H. [1 ]
机构
[1] Yeungnam Univ, Nonlinear Dynam Grp, Dept Elect Engn, Kyongsan 712749, South Korea
[2] Samsung Elect Co Ltd, Div Mobile Commun, Digital Media & Commun, Suwon, Gyeonggi Do, South Korea
[3] Pohang Univ Sci & Technol, Dept Elect & Elect Engn, Pohang 790784, South Korea
[4] Daegu Univ, Sch Elect Engn, Kyongsan, South Korea
关键词
Hopfield neural network; H-infinity passivity; Convex problem; LMI; TIME-VARYING DELAYS; DEPENDENT ASYMPTOTIC STABILITY; CRITERIA; SYSTEM;
D O I
10.1016/j.amc.2010.12.100
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
This paper considers the problem of passivity-based controller design for Hopfield neural networks. By making use of a convex representation of nonlinearities, a feedback control scheme based on passivity and Lyapunov theory is presented. A criterion for existence of the controller is given in terms of linear matrix inequality (LMI), which can be easily solved by a convex optimization problem. An example and its numerical simulation are given to show the effectiveness of the proposed method. (C) 2010 Elsevier Inc. All rights reserved.
引用
收藏
页码:6168 / 6175
页数:8
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