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Fault Detection Filtering Design for Discrete-Time Interval Type-2 T–S Fuzzy Systems in Finite Frequency Domain

Meng Wang, Gang Feng, Jianbin Qiu, Huaicheng Yan, Hao Zhang

2020IEEE Transactions on Fuzzy Systems48 citationsDOI

Abstract

This article focuses on the problem of fault detection filtering design for discrete-time interval type-2 Takagi-Sugeno (T-S) fuzzy systems in finite frequency domain. Considering the fact that external disturbances and faults are usually reside in finite frequency ranges, the finite frequency H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> and H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-</sub> performances are introduced to reflect the disturbance robustness and fault sensitiveness in finite frequency domain, respectively. Based on discrete-time Fourier transform and its properties, finite frequency performance analysis results are first obtained. Then, by exploiting the information on upper and lower membership functions, the membership-function-dependent filtering design conditions in the form of linear matrix inequalities are established for discrete-time interval type-2 T-S fuzzy systems in finite frequency domain. With the obtained filter, a fault detection scheme is then proposed and it is shown that the resulting fault detection system is asymptotically stable with prescribed finite frequency H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> and H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-</sub> performances. Finally, the effectiveness of the proposed method is validated by simulation studies.

Topics & Concepts

Frequency domainRobustness (evolution)Fuzzy logicAlgorithmFault detection and isolationDiscrete frequency domainComputer scienceMathematicsControl theory (sociology)Artificial intelligenceMathematical analysisControl (management)BiochemistryChemistryGeneActuatorFuzzy Logic and Control SystemsNeural Networks and ApplicationsChaos control and synchronization