Non-fragile state estimation for discrete-time neural network system with randomly occurring sensor saturations

被引：0
|
作者：
Bao Wendong [1 ]
Li Jianning [1 ]
Lv Meilei [1 ,2 ]
Cai Jianping [1 ]
Wen Chenglin [1 ]
机构：
[1] Hangzhou Dianzi Univ, Sch Automat, Hangzhou 310018, Zhejiang, Peoples R China
[2] Quzhou Univ, Inst Elect & Informat Engn, Quzhou 324000, Zhejiang, Peoples R China
来源：
PROCEEDINGS OF THE 36TH CHINESE CONTROL CONFERENCE (CCC 2017) | 2017年
基金：
中国国家自然科学基金;
关键词：
Non-fragile state estimation; Time delays; Nonlinearity; Sensor saturations; LINEAR-SYSTEMS; ASYMPTOTIC STABILITY; VARYING DELAYS; STABILIZATION; ACTUATOR; CRITERIA; SUBJECT;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper investigates the problem for the non-fragile state estimation of discrete-time neural network system with randomly occurring sensor saturations and time delays. In order to show the possible gain variations occurring in complex environments, a non-fragile state estimator is designed to ensure the estimation error converges to zero exponentially. And, by using a sensor saturation function to deals with the sensor saturation phenomenon. Then, Lyapunnov-Krasovskii functional approach is proposed, sufficient conditions are established to guarantee the existence of the desired state estimator. Finally, a numerical example is given to illustrate the effectiveness of the proposed method.
引用
收藏
页码：3089 / 3094
页数：6
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