Paper Info
Title
Fault Detection and Isolation for a Class of Nonlinear Systems Based on Gerschgorin Theorem and Optimization Approach
Abstract
This article is concerned with the fault detection and isolation (FDI) problem for a class of nonlinear systems described by the T–S fuzzy models. Based on the concept of minimum unobservability subspace and geometric property of factor space, a set of FDI filters where each residual is only affected by one fault and completely decoupled from other faults is designed. Furthermore, in the decoupling space, the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$H_{\infty }/H_{-}$ </tex-math></inline-formula> performance indexes are provided to enhance the sensitivity of residual to faults and robustness to disturbances. In particular, to solve the nonconvex filter design problem caused by introducing the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$H_{-}$ </tex-math></inline-formula> index, the Gerschgorin theorem is first used to linearize the corresponding filter design conditions in the outer region of a ball. Then, the FDI filter design problem is converted into a convex optimization one, which is solved via the linear matrix inequality (LMI) control Toolbox, and the advantages and effectiveness of the proposed FDI method are verified through two simulation examples.
Year
DOI
Venue
2022
10.1109/TSMC.2021.3129812
IEEE Transactions on Systems, Man, and Cybernetics: Systems
Keywords
DocType
Volume
Convex optimization approach,fault detection and isolation (FDI),Gerschgorin theorem,nonlinear systems
Journal
52
Issue
ISSN
Citations 
9
2168-2216
0
PageRank 
References 
Authors
0.34
35
3
Name
Order
Citations
PageRank
Jie Sun100.34
P. Liu2508.37
Xiao-Jian Li326413.82