Sampled-data H∞ fuzzy filtering for nonlinear systems with missing measurements

被引:25
作者
Koo, Geun Bum [1 ]
Park, Jin Bae [2 ]
Joo, Young Hoon [3 ]
机构
[1] Kongju Natl Univ, Div Elect Elect & Control Engn, Kong Ju 314701, South Korea
[2] Yonsei Univ, Dept Elect & Elect Engn, Seoul 120749, South Korea
[3] Kunsan Natl Univ, Dept Control & Robot Engn, Kunsan 573701, Chonbuk, South Korea
基金
新加坡国家研究基金会;
关键词
Sampled-data H-infinity fuzzy filtering; Nonlinear system; Missing measurement; Exponential mean-square stability; Linear matrix inequality; LYAPUNOV FUNCTION; STABILIZATION; STABILITY; DESIGN;
D O I
10.1016/j.fss.2016.04.016
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
In this paper, a sampled-data H-infinity fuzzy filtering problem is considered for nonlinear systems with missing measurements. The nonlinear sampled-data system and missing measurements are assumed to be represented by a Takagi-Sugeno (T-S) fuzzy system and an independent, identically distributed Bernoulli random process, respectively. Based on the fuzzy system, the H-infinity fuzzy filtering problem is formulated to design the sampled-data fuzzy filter. By using the exponential mean-square stability definition, the stability condition with an H-infinity performance is guaranteed for the fuzzy system with the sampled-data fuzzy filter, and its sufficient condition is converted into the linear matrix inequality (LMI) format. Finally, an example is provided to verify the effectiveness of the proposed fuzzy filtering technique. (C) 2016 Elsevier B. V. All rights reserved.
引用
收藏
页码:82 / 98
页数:17
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