Nonlinear H∞ control of structured uncertain stochastic neural networks with discrete and distributed time varying delays

doi:10.1088/1674-1056/17/4/059

中国物理B ›› 2008, Vol. 17 ›› Issue (4): 1506-1512.doi: 10.1088/1674-1056/17/4/059

Nonlinear H_∞ control of structured uncertain stochastic neural networks with discrete and distributed time varying delays

张卫东¹, 陈狄岚²

(1)Department of Automation, Shanghai Jiaotong University, Shanghai 200030, China; (2)Department of Automation, Shanghai Jiaotong University, Shanghai 200030, China；Division of Basic Courses, Shanghai Maritime University, Shanghai 200135, China

收稿日期:2007-03-27 修回日期:2007-11-10 出版日期:2008-04-20 发布日期:2008-04-20
基金资助:
Project is supported in part by the National Natural Science Foundation of China (Grant No 60474031), NCET (04-0383), the State Key Development Program for Basic Research of China (Grant No 2002cb312200-3), the Shanghai `Phosphor' Foundation (Grant No 04Q

Nonlinear H_∞ control of structured uncertain stochastic neural networks with discrete and distributed time varying delays

Chen Di-Lan(陈狄岚)^a)b)^† and Zhang Wei-Dong(张卫东)^a)

^a Department of Automation, Shanghai Jiaotong University, Shanghai 200030, China; ^b Division of Basic Courses, Shanghai Maritime University, Shanghai 200135, China

Received:2007-03-27 Revised:2007-11-10 Online:2008-04-20 Published:2008-04-20
Supported by:
Project is supported in part by the National Natural Science Foundation of China (Grant No 60474031), NCET (04-0383), the State Key Development Program for Basic Research of China (Grant No 2002cb312200-3), the Shanghai `Phosphor' Foundation (Grant No 04Q

摘要/Abstract

摘要： This paper is concerned with the problem of robust H_infty control for structured uncertain stochastic neural networks with both discrete and distributed time varying delays. A sufficient condition is presented for the existence of H_infty control based on the Lyapunov stability theory. The stability criterion is described in terms of linear matrix inequalities (LMIs), which can be easily checked in practice. An example is provided to demonstrate the effectiveness of the proposed result.

关键词: delayed neural networks (DNNs), stochastic systems, Lyapunov functional, linear matrix inequality

Abstract: This paper is concerned with the problem of robust $H_{\infty}$ control for structured uncertain stochastic neural networks with both discrete and distributed time varying delays. A sufficient condition is presented for the existence of $H_{\infty}$ control based on the Lyapunov stability theory. The stability criterion is described in terms of linear matrix inequalities (LMIs), which can be easily checked in practice. An example is provided to demonstrate the effectiveness of the proposed result.

Key words: delayed neural networks (DNNs), stochastic systems, Lyapunov functional, linear matrix inequality

中图分类号: (Matrix theory)

02.10.Yn

02.50.Ey (Stochastic processes) 02.60.Dc (Numerical linear algebra) 07.05.Mh (Neural networks, fuzzy logic, artificial intelligence)

陈狄岚, 张卫东. Nonlinear H_∞ control of structured uncertain stochastic neural networks with discrete and distributed time varying delays[J]. 中国物理B, 2008, 17(4): 1506-1512.

Chen Di-Lan(陈狄岚) and Zhang Wei-Dong(张卫东). Nonlinear H_∞ control of structured uncertain stochastic neural networks with discrete and distributed time varying delays[J]. Chin. Phys. B, 2008, 17(4): 1506-1512.

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Nonlinear H_∞ control of structured uncertain stochastic neural networks with discrete and distributed time varying delays

Nonlinear H_∞ control of structured uncertain stochastic neural networks with discrete and distributed time varying delays

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