Fuzzy Filter for Nonlinear Sampled-data Systems: Intelligent Digital Redesign Approach

被引：6
作者：
Kim, Ho Jun [1 ]
Park, Jin Bae [1 ]
Joo, Young Hoon [2 ]
机构：
[1] Yonsei Univ, Dept Elect & Elect Engn, Seoul 120749, South Korea
[2] Gunsan Natl Univ, Dept Control & Robot Engn, Gunsan 573701, Chonbuk, South Korea
来源：
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS | 2017年 / 15卷 / 02期
基金：
新加坡国家研究基金会;
关键词：
Fuzzy filter; intelligent digital redesign (IDR); linear matrix inequality (LMI); sampled-data systems; Takagi-Sugeno (T-S) fuzzy model; FEEDBACK; STABILIZATION; DESIGN;
D O I：
10.1007/s12555-015-0437-9
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 presents a fuzzy filter design method for nonlinear sampled-data systems using an intelligent digital redesign (IDR) technique. Based on a Takagi-Sugeno (T-S) fuzzy model, discretized closed-loop systems with pre-designed analog fuzzy and digital fuzzy filters are presented. An IDR problem is given to guarantee both state-matching condition and asymptotic stability. Sufficient conditions for solving the IDR problem are proposed and are derived in terms of linear matrix inequalities (LMIs). Finally, a simulation example is given to show the effectiveness of the proposed method.
引用
收藏
页码：603 / 610
页数：8
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