fuzzy filter for non-linear sampled-data systems under imperfect premise matching

作     者：Ho Jun Kim Jin Bae Park Young Hoon Joo 

作者机构：Department of Electrical and Electronic Engineering Yonsei University Seoul 120-749 Republic of Korea Department of Control and Robot Engineering Kunsan National University Kunsan Chonbuk 573-701 Republic of Korea 

出 版 物：《IET Control Theory & Applications》 

年 卷 期：2017年第11卷第5期

页      面：747-755页

学科分类：0808[工学-电气工程] 08[工学] 

基　　金：National Research Foundation of Korea: 2015R1A2A2A01007545  2016R1A6A1A03013567 

主　　题：H∞ filters pattern matching fuzzy set theory linear matrix inequalities H∞ fuzzy filter nonlinear sampled data systems imperfect premise matching Takagi-Sugeno fuzzy model error system asymptotic stability Lyapunov sense linear matrix inequalities 

摘      要：This study proposes an fuzzy filtering technique for non-linear sampled-data systems that are represented on the basis of the Takagi–Sugeno fuzzy model. To improve the performance of the fuzzy filter, an imperfect premise matching condition is considered. An error system between the non-linear system and the fuzzy filter is constructed. In addition, sufficient conditions for showing asymptotic stability and guaranteeing disturbance attenuation performance are proposed in a Lyapunov sense and derived in terms of linear matrix inequalities. Finally, the feasibility of the proposed technique is demonstrated using two simulation examples.