Interval type-2 fuzzy logic systems (IT2 FLSs) have demonstrated better abilities to handle
uncertainties than their type-1 (T1) counterparts in many applications; however, the high …

Data, as being the vital input of system modelling, contain dissimilar level of imprecision that
necessitates different modelling approaches for proper analysis of the systems. Numbers …

This paper presents an integrated interval type-2 fuzzy logic approach that simultaneously
models and controls an underactuated mobile two-wheeled inverted pendulum (MTWIP) …

Increasingly, genetic algorithms (GAs) are used to optimize the parameters of fuzzy logic
controllers (FLCs). Although GAs provide a systematic design approach, the optimization …

Interval type-2 fuzzy logic controllers (IT2 FLCs) have been attracting great research
interests recently. There are many decisions to be made in designing an IT2 FLC. One of …

A type-2 fuzzy set is characterized by a concept called footprint of uncertainty (FOU). It
provides the extra mathematical dimension that equips type-2 fuzzy logic systems (FLSs) …

This tutorial illustrates the basic ideas of interval type-2 (IT2) fuzzy sets and systems, and
provides a Matlab implementation of IT2 fuzzy logic system (FLS). One obstacle in learning …

This book presents fuzzy logic and LabVIEW FGPA for designing fuzzy logic controllers. This
is a book for implementing fuzzy logic controllers in LabVIEW FPGAs. Despite the FPGA's …

There has been an increasing amount of research on type-2 fuzzy logic systems (FLSs)
recently. The interest is fueled by results demonstrating that type-2 fuzzy sets offer a …

In the deployment of interval type-2 fuzzy systems, one of the most important steps is the
type reduction. The commonly used center of sets type reducer requires the solution of two …