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

作　　者：陈狄岚 张卫东 

机构地区：[1]Department of Automation,Shanghai Jiaotong University [2]Division of Basic Courses,Shanghai Maritime University

出　　处：《Chinese Physics B》2008年第4期1506-1512,共7页中国物理B（英文版）

基　　金：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 04QMH1405);Australia-China Special Fund for Scientific & Technological Cooperation

摘　　要：This paper is concerned with the problem of robust H∞ 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∞ 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.This paper is concerned with the problem of robust H∞ 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∞ 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 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程] TP13[自动化与计算机技术—控制科学与工程]