Fault detection in nonlinear systems based on type-2 fuzzy sets and bat optimization algorithm

In this paper, a new method of fault detection is proposed based on interval type-2 fuzzy systems. The main idea is to provide a confident span using interval type-2 fuzzy sets. Bat algorithm, as a metaheuristic method, is used to optimize the parameters of the system. In other words, upper and lowe...

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Bibliographic Details
Published inJournal of intelligent & fuzzy systems Vol. 28; no. 1; pp. 179 - 187
Main Authors Safarinejadian, Behrouz, Bagheri, Bahareh, Ghane, Parisa
Format Journal Article
LanguageEnglish
Published London, England SAGE Publications 01.01.2015
Subjects
Algorithms
Dynamical systems
Fault detection
Fuzzy logic
Fuzzy set theory
Fuzzy systems
Intervals
Nonlinear dynamics
Optimization
interval type-2 fuzzy
Fuzzy system
bat algorithm
fault detection
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ISSN1064-1246
1875-8967
DOI10.3233/IFS-141288

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Summary:In this paper, a new method of fault detection is proposed based on interval type-2 fuzzy systems. The main idea is to provide a confident span using interval type-2 fuzzy sets. Bat algorithm, as a metaheuristic method, is used to optimize the parameters of the system. In other words, upper and lower bounds of the interval type-2 fuzzy system are estimated by means of two optimal fuzzy functions. The proposed fault detection method has been tested in a non-linear system, a two-tank with a fluid flow. Simulation results show that the proposed method is very strong and effective.
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ISSN:1064-1246
1875-8967
DOI:10.3233/IFS-141288