典型文献
Fuzzy Set-Membership Filtering for Discrete-Time Nonlinear Systems
文献摘要：
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 filtering.First,an improved T-S fuzzy model is introduced to achieve highly accurate approximation via an affine model under each fuzzy rule.Then,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 filtering.Under 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 error.Real-time recursive algorithms are given to find the minimal ellipsoid containing the true state.Finally,the proposed optimization approaches are validated via numerical simulations of a one-dimensional and a three-dimensional discrete-time nonlinear systems.
文献关键词：
中图分类号：
作者姓名：
Jingyang Mao;Xiangyu Meng;Derui Ding
作者机构：
Department of Control Science and Engineering,University of Shanghai for Science and Technology,Shanghai 200093,China;Division of Electrical and Computer Engineering,Louisiana State University,Baton Rouge,LA,70803 USA ;School of Science,Computing and Engineering Technologies,Swinburne University of Technology,Melbourne,VIC 3122,Australia
文献出处：
引用格式：
[1]Jingyang Mao;Xiangyu Meng;Derui Ding-.Fuzzy Set-Membership Filtering for Discrete-Time Nonlinear Systems)[J].自动化学报（英文版）,2022(06):1026-1036
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AB值：
0.641195
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