Fault tree analysis (FTA) is one of the most popular failure analysis techniques that reveal
the potential pathways leading to systems or components failure. It has been widely …

This paper presents a review of the central theories involved in hybrid models based on
fuzzy systems and artificial neural networks, mainly focused on supervised methods for …

Industry 4.0 provides substantial opportunities to ensure a safer environment through online
monitoring, early detection of faults, and preventing the faults to failures transitions. Decision …

Abstract The automation of Fault Detection and Diagnosis (FDD) is a central task for many
industries today. A myriad of methods are in use, although the most recent leading …

Modern data-driven fault detection and diagnosis (FDD) techniques show impressive high
diagnostic accuracy in recognizing various air handling units (AHUs) faults. Most existing …

This paper provides an in-depth review of the optimal design of type-1 and type-2 fuzzy
inference systems (FIS) using five well known computational frameworks: genetic-fuzzy …

In many practical applications of classifiers, not only high accuracy but also high
interpretability is required. Among a wide variety of existing classifiers, Takagi–Sugeno …

Fault detection, isolation and optimal control have long been applied to industry. These
techniques have proven various successful theoretical results and industrial applications …

As one of the three pillars in computational intelligence, fuzzy systems are a powerful
mathematical tool widely used for modelling nonlinear problems with uncertainties. Fuzzy …

This paper presents an adaptive neural network (NN)-based fault-tolerant control approach
for the compensation of actuator failures in nonlinear systems with time-varying delay. The …