文献类型：期刊文献

英文题名：H∞ filtering for nonlinear networked systems with randomly occurring distributed delays, missing measurements and sensor saturation

作者：Yan, Huaicheng[1];Qian, Fengfeng[1];Yang, Fuwen[2];Shi, Hongbo[1]

机构：[1]East China Univ Sci & Technol, Sch Informat Sci & Engn, Minist Educ, Key Lab Adv Control & Optimizat Chem Proc, Shanghai 200237, Peoples R China;[2]Griffith Univ, Sch Engn, Gold Coast, Qld 4222, Australia

年份：2016

卷号：370

起止页码：772

外文期刊名：INFORMATION SCIENCES

收录：;EI(收录号：20164102888562);WOS:【SCI-EXPANDED(收录号:WOS:000389399600051)】；

基金：This work is supported by the National Natural Science Foundation of China (61174064, 61272064, 61273026), Shanghai Pujiang Program (14PJ1409000), the Fundamental Research Funds for Central Universities, Zhejiang Open Foundation of the Most Important Subjects and the Open Research Fund for Key Laboratory of Embedded System and Service Computing, Ministry of Education, Tongji University.

语种：英文

外文关键词：H-infinity filtering; Nonlinearities; Distributed delays; Missing measurements; Sensor saturation

摘要：This paper is concerned with the H-infinity filtering problem for a class of networked systems subject to randomly occurring distributed state delays, nonlinearities, sensor saturation as well as missing measurements via unreliable communication channels. The output measurements are affected by sensor saturation which is described by sector-nonlinearities. The missing measurement is modeled as a linear random variable satisfying the Bernoulli distribution, and the nonlinearities with the form of global Lipschitz cover the well-known nonlinear functions. The purpose of the addressed problem is to design a full-order filter such that, in the simultaneous presence of distributed delays, randomly occurring nonlinearities, sensor saturation and missing measurements, the filtering dynamic system is guaranteed to be exponentially mean-square stable, and the H-infinity filtering performance index is achieved. A sufficient condition for the solution of the addressed problem is derived, and the explicit expression of the desired filter gains is described in terms of the solution to linear matrix inequality (LMI). Finally, a numerical example is provided to show the effectiveness of the designed method. (C) 2015 Elsevier Inc. All rights reserved.