Decentralized Fuzzy Observer-Based Fault Estimation for Nonlinear Large-Scale Systems

This paper presents a fault estimation technique based on the decentralized fuzzy observer for nonlinear large-scale systems, which are considered to be consisted of fuzzy subsystems and uncertain interconnections. Based on a Takagi–Sugeno fuzzy model for the subsystems of the large-scale...

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Bibliographic Details
Main Author: Geun Bum Koo
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10460537/
Description
Summary:This paper presents a fault estimation technique based on the decentralized fuzzy observer for nonlinear large-scale systems, which are considered to be consisted of fuzzy subsystems and uncertain interconnections. Based on a Takagi&#x2013;Sugeno fuzzy model for the subsystems of the large-scale system and the decentralized fuzzy observer, the <inline-formula> <tex-math notation="LaTeX">$H_{\infty }$ </tex-math></inline-formula> performance of the fault estimation problem is established by using the estimation error model. By using <inline-formula> <tex-math notation="LaTeX">$H_{\infty }$ </tex-math></inline-formula> performance inequalities to address the fault estimation problem, the decentralized fuzzy observer design techniques are proposed to guarantee the fault estimation conditions. Also, sufficient conditions of observer design are converted into the linear matrix inequality formats. Finally, an example is provided to verify the effectiveness of the proposed decentralized fuzzy observer design techniques for fault estimation.
ISSN:2169-3536