State and Fault Interval Estimation for Discrete-time Takagi-Sugeno Fuzzy Systems via Intermediate Observer Base on Zonotopic Analysis

This short paper studies state and fault interval estimation method for discrete-time Takagi-Sugeno fuzzy systems. First, a novel intermediate observer via T-N-L structure with H_{\infty } performance is designed. The intermediate observer proposed is designed with a higher degree of freedom due to...

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Bibliographic Details
Published in:IEEE transactions on fuzzy systems 2024-09, p.1-6
Main Authors: Zhang, Lulin, Li, Zhuoxue, Li, Yi, Dong, Jiuxiang
Format: Article
Language:English
Subjects:
<inline-formula xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"> <tex-math notation="LaTeX"> H_{\infty }</tex-math> </inline-formula> performance
Circuit faults
Estimation
Fuzzy systems
intermediate observer
Linear matrix inequalities
Nonlinear systems
Observers
State and fault interval estimation
Takagi-Sugeno fuzzy model
Vectors
zonotopic analysis
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Summary:This short paper studies state and fault interval estimation method for discrete-time Takagi-Sugeno fuzzy systems. First, a novel intermediate observer via T-N-L structure with H_{\infty } performance is designed. The intermediate observer proposed is designed with a higher degree of freedom due to the introduction of two auxiliary variables. Second, based on this novel intermediate observer, zonotopic analysis is utilized to give a range of the effects of unknown inputs and fault derivatives on state and fault estimation, thus interval estimation results for state and fault are obtained. The effectiveness of the proposed method is verified by a DC motor-controlled inverted pendulum system.
ISSN:1063-6706
1941-0034
DOI:10.1109/TFUZZ.2024.3459642