具有混合时滞和丢包的不确定神经网络同步  

Synchronization of Uncertain Neural Network with Mixed Delays and Packet Losses

作　　者：葛超 刘增帅 郭文 苏皓 GE Chao;LIU Zengshuai;GUO Wen;SU Hao(College of Electrical Engineering,North China University of Science and Technology,Tangshan Hebei 063210,China;Tangshan Key Laboratory of Semiconductor Integrated Circuits,Tangshan Hebei 063210,China)

机构地区：[1]华北理工大学电气工程学院,河北唐山063210 [2]唐山市半导体集成电路重点实验室,河北唐山063210

出　　处：《指挥与控制学报》2023年第5期566-572,共7页Journal of Command and Control

基　　金：河北省自然科学基金(F2021209006)资助。

摘　　要：研究了一类具有丢包现象的不确定神经网络的指数同步问题.所提出的Lyapunov-Krasovskii泛函能够充分利用系统信息,并且采用一种改进的积分不等式,得到线性矩阵不等式形式的稳定性准则来求解控制器.所得到的结果保守性较小,能够实现更大的衰减速率.采用一种切换系统的方法来分析系统指数稳定性,将存在丢包的同步误差系统建模为标准的切换系统模型,推导出和丢包率相关的平均驻留时间切换条件.最后通过两个数值算例验证了理论的有效性.The exponential synchronization problem of uncertain neural networks with the phenomenon of packet losses is studied.The proposed functional Lyapunov-Krasovskii can make full use of the system information.An improved integrating inequality is utilized to obtain the stability criterion formed in linear matrix inequalities and to solve the controller.The obtained result is of low conservatism,a larger attenuation rate can be realized.A switch system method is used to analyze the exponential stability of the system,the synchronization errorm system with packet losses is modeled as a standard switch system model.The mean residence time related to the packet loss rate is deduced.Finally,the effectiveness of the theory is verified by two numerical examples.

关 键 词：同步 平均驻留时间 神经网络 切换系统 丢包 不确定性 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]