泄漏时滞神经网络的改进滞后状态反馈控制  

Improved Delayed State-feedback Control for St abilization of Neural Net works with Leakage Delay

作　　者：韩彦武 汤红吉[2] HAN Yan-wu;TANG Hong-ji(Nantong University Xinglin College,Nantong 226236,China;School of Science,Nantong University,Nantong 226009,China)

机构地区：[1]南通大学杏林学院,江苏南通226236 [2]南通大学理学院,江苏南通226009

出　　处：《数学的实践与认识》2021年第21期303-312,共10页Mathematics in Practice and Theory

摘　　要：考虑了具有泄露时滞神经网络的滞后状态反馈指数镇定问题.通过构造适当的增广Lyapunov-krasovskii泛函,借助于积分不等式和改进倒凸组合技巧,以线性不等式的形式得出神经网络指数镇定的充分条件.最后,数值算例表明方法的有效性.In this paper,the problem of delayed state-feedback exponential stabilization is investigated for neural networks with leakage delay.By constructing an appropriate augmented Lyapunov krasovskii functional,using the integral inequality and the improved reciprocal convex combination technique,the sufficient conditions for exponential stabilization of neural networks are obtained in the form of linear matrix inequalities.Finally,numerical examples show the effectiveness of the proposed method.

关 键 词：泄漏时滞 增广Lyapunov-krasovskii泛函 线性矩阵不等式 状态反馈控制 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]