Asynchronous Partially Mode-Dependent Filtering of Network-Based MSRSNSs With Quantized Measurement

被引：30

作者：

Cheng, Jun ^{[1
]}

Park, Ju H. ^{[2
]}

Cao, Jinde ^{[3
,4
]}

Qi, Wenhai ^{[5
]}

机构：

[1] Guangxi Normal Univ, Coll Math & Stat, Guilin 541006, Peoples R China

[2] Yeungnam Univ, Dept Elect Engn, Gyongsan 38541, South Korea

[3] Southeast Univ, Jiangsu Prov Key Lab Networked Collect Intelligen, Nanjing 211189, Peoples R China

[4] Southeast Univ, Sch Math, Nanjing 211189, Peoples R China

[5] Qufu Normal Univ, Sch Engn, Rizhao 276826, Peoples R China

来源：

IEEE TRANSACTIONS ON CYBERNETICS | 2020年 / 50卷 / 08期

基金：

新加坡国家研究基金会; 中国国家自然科学基金;

关键词：

Asynchronous filtering; l(2)-l(infinity) filter; Markovian switching systems; quantization effect; MARKOV JUMP SYSTEMS; NONLINEAR-SYSTEMS; FEEDBACK-CONTROL; NEURAL-NETWORKS; STABILITY; SUBJECT; DESIGN; FAULTS; DELAYS; RESET;

D O I：

10.1109/TCYB.2019.2939830

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 article addresses the issue of asynchronous partially mode-dependent filtering for networked Markov switching repeated scalar nonlinear systems (MSRSNSs) subject to quantized measurements (QMs). Especially, a novel partially mode-dependent filter (PMDF) is constructed, where the signal transmission of a filter mode occurred randomly and is modeled by a Bernoulli distributed sequence. The designed PMDF is different from state mode, which is governed by an asynchronous switching rule. By utilizing a diagonally dominant-type Lyapunov functional (DDTLF), sufficient conditions ensure that the existence of the PMDF and the l(2)-l(infinity) performance index are derived. Finally, an economic example is adopted to substantiate the applicability of the developed theoretical results.

引用

页码：3731 / 3739

页数：9

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