Fuzzy filtering‐based fault detection for a class of discrete‐time conic‐type nonlinear systems

Fuzzy filtering‐based fault detection for a class of discrete‐time conic‐type nonlinear systems

Abstract The authors investigates the problem of fuzzy fault detection filter (FFDF) design for a class of discrete‐time conic‐type nonlinear systems. By applying Takagi–Sugeno fuzzy models, the conic‐type dynamic FFDF system is established. Then, utilizing the Lyapunov function method to find a suf...

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Main Authors: Jiancheng Wang, Shuping He
Format: Article
Language:English
Published: Wiley 2021-05-01
Series:IET Signal Processing
Online Access:https://doi.org/10.1049/sil2.12016
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spelling doaj-377e34c053224cb1ad8e13a5352c9e942021-08-02T08:25:34ZengWileyIET Signal Processing1751-96751751-96832021-05-0115315316110.1049/sil2.12016Fuzzy filtering‐based fault detection for a class of discrete‐time conic‐type nonlinear systemsJiancheng Wang0Shuping He1Key Laboratory of Intelligent Computing and Signal Processing (Ministry of Education) School of Electrical Engineering and Automation Anhui University Hefei People's Republic of ChinaKey Laboratory of Intelligent Computing and Signal Processing (Ministry of Education) School of Electrical Engineering and Automation Anhui University Hefei People's Republic of ChinaAbstract The authors investigates the problem of fuzzy fault detection filter (FFDF) design for a class of discrete‐time conic‐type nonlinear systems. By applying Takagi–Sugeno fuzzy models, the conic‐type dynamic FFDF system is established. Then, utilizing the Lyapunov function method to find a sufficient condition which ensures that the conic‐type dynamic FFDF system is asymptotically stable. After that, using linear matrix inequalities techniques, the FFDF design problem is transformed into an optimization algorithm. Finally, the simulation results demonstrate that the designed FFDF is effective for detecting the faults.https://doi.org/10.1049/sil2.12016
collection DOAJ
language English
format Article
sources DOAJ
author Jiancheng Wang
Shuping He
spellingShingle Jiancheng Wang
Shuping He
Fuzzy filtering‐based fault detection for a class of discrete‐time conic‐type nonlinear systems
IET Signal Processing
author_facet Jiancheng Wang
Shuping He
author_sort Jiancheng Wang
title Fuzzy filtering‐based fault detection for a class of discrete‐time conic‐type nonlinear systems
title_short Fuzzy filtering‐based fault detection for a class of discrete‐time conic‐type nonlinear systems
title_full Fuzzy filtering‐based fault detection for a class of discrete‐time conic‐type nonlinear systems
title_fullStr Fuzzy filtering‐based fault detection for a class of discrete‐time conic‐type nonlinear systems
title_full_unstemmed Fuzzy filtering‐based fault detection for a class of discrete‐time conic‐type nonlinear systems
title_sort fuzzy filtering‐based fault detection for a class of discrete‐time conic‐type nonlinear systems
publisher Wiley
series IET Signal Processing
issn 1751-9675
1751-9683
publishDate 2021-05-01
description Abstract The authors investigates the problem of fuzzy fault detection filter (FFDF) design for a class of discrete‐time conic‐type nonlinear systems. By applying Takagi–Sugeno fuzzy models, the conic‐type dynamic FFDF system is established. Then, utilizing the Lyapunov function method to find a sufficient condition which ensures that the conic‐type dynamic FFDF system is asymptotically stable. After that, using linear matrix inequalities techniques, the FFDF design problem is transformed into an optimization algorithm. Finally, the simulation results demonstrate that the designed FFDF is effective for detecting the faults.
url https://doi.org/10.1049/sil2.12016
work_keys_str_mv AT jianchengwang fuzzyfilteringbasedfaultdetectionforaclassofdiscretetimeconictypenonlinearsystems
AT shupinghe fuzzyfilteringbasedfaultdetectionforaclassofdiscretetimeconictypenonlinearsystems
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