2022
DOI: 10.3390/machines10050347
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Fault Detection for Interval Type-2 T-S Fuzzy Networked Systems via Event-Triggered Control

Abstract: This paper investigates the event-triggered fault diagnosis (FD) problem for interval type-2 (IT2) Takagi–Sugeno (T-S) fuzzy networked systems. Firstly, an FD fuzzy filter is proposed by using IT2 T-S fuzzy theory to generate a residual signal. This means that the FD filter premise variable needs to not be identical to the nonlinear networked systems (NNSs). The evaluation functions are referenced to determine the occurrence of system faults. Secondly, under the event-triggered mechanism, a fault residual syst… Show more

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Cited by 4 publications
(2 citation statements)
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“…Traditional maintenance schedules are often based on fixed intervals, which may not reflect the actual condition of the engine. In contrast, FLC-based scheduling is dynamic and adapts to the real-time state of the engine [24][25][26][27].…”
Section: Predictive Maintenance Using Fuzzy Logicmentioning
confidence: 99%
“…Traditional maintenance schedules are often based on fixed intervals, which may not reflect the actual condition of the engine. In contrast, FLC-based scheduling is dynamic and adapts to the real-time state of the engine [24][25][26][27].…”
Section: Predictive Maintenance Using Fuzzy Logicmentioning
confidence: 99%
“…In [7], the authors investigated the event-triggered fault diagnosis (FD) problem. Firstly, an FD fuzzy filter was proposed by using IT2 T-S fuzzy theory to generate a residual signal.…”
mentioning
confidence: 99%