文章基本信息

标题：Robust Zonotopic Observer Design: Avoiding Unmeasured Premise Variables for Takagi-Sugeno Fuzzy Systems
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作者：Masoud Pourasghar ; Anh-Tu Nguyen ; Thierry-Marie Guerra 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2021
卷号：54
期号：4
页码：68-73
DOI：10.1016/j.ifacol.2021.10.012
语种：English
出版社：Elsevier
摘要：AbstractThis paper addresses the design of a robust set-based interval observer for a nonlinear discrete-time system affected by system uncertainty (state disturbance and measurement noise) using a Takagi-Sugeno (TS) fuzzy model including an unmeasurable premise variable. The effect of unmeasurable premise variable and uncertainties is considered as of unknown but bounded nature, i.e., in the set-membership framework. A zonotopic representation of a set towards reducing set operations to simple matrix calculations is used to bound the state estimation provided by the interval observer-based approach. Furthermore, the criterion-based approach and H∞performance technique are considered in order to compute the observer gain to achieve robustness. Finally, an example is employed to both illustrate and discuss the effectiveness of the proposed approach.
关键词：KeywordsTakagi-Sugeno fuzzy systemsnonlinear estimationinterval observerszonotopeH∞performancelinear matrix inequality