Fuzzy Set-Membership Filtering for Discrete-Time Nonlinear Systems

作     者：Jingyang Mao Xiangyu Meng Derui Ding Jingyang Mao;Xiangyu Meng;Derui Ding

作者机构：Department of Control Science and EngineeringUniversity of Shanghai for Science and TechnologyShanghai 200093China Division of Electrical and Computer EngineeringLouisiana State UniversityBaton RougeLA70803 USA IEEE School of ScienceComputing and Engineering TechnologiesSwinburne University of TechnologyMelbourneVIC 3122Australia 

出 版 物：《IEEE/CAA Journal of Automatica Sinica》 (自动化学报（英文版）)

年 卷 期：2022年第9卷第6期

页      面：1026-1036页

核心收录：

学科分类：080902[工学-电路与系统] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 

基　　金：supported in part by the National Natural Science Foundation of China(61973219,61933007,62073158) the China Scholarship Council(201908310148) 

主　　题：Affine model membership functions set-membership filtering stability Takagi-Sugeno fuzzy modeling 

摘      要：In this article,the problem of state estimation is addressed for discrete-time nonlinear systems subject to additive unknown-but-bounded noises by using fuzzy set-membership ***,an improved T-S fuzzy model is introduced to achieve highly accurate approximation via an affine model under each fuzzy ***,compared to traditional prediction-based ones,two types of fuzzy set-membership filters are proposed to effectively improve filtering performance,where the structure of both filters consists of two parts:prediction and *** the locally Lipschitz continuous condition of membership functions,unknown membership values in the estimation error system can be treated as multiplicative noises with respect to the estimation ***-time recursive algorithms are given to find the minimal ellipsoid containing the true ***,the proposed optimization approaches are validated via numerical simulations of a one-dimensional and a three-dimensional discrete-time nonlinear systems.