It is known that type-2 fuzzy sets let us to model and to minimize the effects of uncertainties in rule-based fuzzy logic system (FLS). While a type-2 FLS has the capability to model more complex relationships, the output of a type-2 fuzzy inference...

In this paper a new fuzzy modeling approach is proposed, which is devoted to discover knowledge from

data and represent it in the form of fuzzy rules. In this approach, the structure identification and parameter ...

One of the main advantages of interval type-2 fuzzy logic systems is their ability to produce prediction intervals as a by-product of the type reduction process. This is especially useful for the design of interval type-2 fuzzy logic systems, where...

This paper proposes a new method for designing Interval Type-2 Fuzzy Logic Systems (IT2 FLSs) considering two issues: first, quality of clustering the output space and secondly, approximating the output of the IT2 FLS based on a new output...

combination of interval type-2

fuzzy logic system (IT2FS) and particle swarm optimization

(PSO) is presented that PSO is used for parameters optimization

of IT2FS membership function. In order to evaluate the

performance of proposed...

Controller design remains an elusive and challenging problem for uncertain nonlinear dynamics. Interval type-2 fuzzy logic systems (IT2FLS) in comparison with type-1 fuzzy logic systems claim to effectively handle system uncertainties especially...

This research examines the emerging role of adaptive interval type-2 fuzzy logic systems (AIT2FLS) versus adaptive type-1 fuzzy logic system (AT1FLS) in vehicle handling by a new nonlinear model of the variable geometry suspension system (VGS) as a...

In this paper, new Interval type-2 fuzzy controllers, which are designed by Sarsa learning, are proposed. The porposed controllers are A2-C0 Takagi-Sugeno-Kang type. Therefore, the antecedent part of rules is formed by ...