This paper deals with the synthesis of adaptive type-2 fuzzy logic controller for a class of single-input single-output system. Due to its ability in serving in universal approximation, the type-2 fuzzy logic system is used to approximate the unknown system dynamics, which will be adjusted according to the on-line adaptation laws deduced from the stability analysis. To ensure the closed loop sy...

This paper proposes a novel fuzzy modeling approach for identification of dynamic systems. A fuzzy model, recurrent interval type-2 fuzzy neural network (RIT2FNN), is constructed by using a recurrent neural network which recurrent weights, mean and standard deviation of the membership functions are updated. The complete back propagation (BP) algorithm tuning equations used to tune the anteceden...

Nonlinear inter-symbol interference leads to significant error rate in nonlinear communication and digital storage channel. In this paper, therefore, a novel recurrent interval type-2 fuzzy neural network with asymmetric membership functions (RT2FNN-A) is proposed for nonlinear channel equalization. The RT2FNN-A uses the interval asymmetric type-2 fuzzy sets and it implements the fuzzy logic sy...

In this paper, we propose a novel recurrent interval type-2 fuzzy neural network with asymmetric membership functions (RT2FNN-A). The RT2FNN-A uses the interval asymmetric type-2 fuzzy sets and it implements the fuzzy logic system (FLS) in a five-layer neural network structure. The RT2FNN-A is modified from the type-2 fuzzy neural network to provide memory elements for capturing the system’s dy...

Type-2 fuzzy sets and complex fuzzy sets are both three dimensional extensions of type-1 fuzzy sets. Complex fuzzy sets come in two forms, the standard form, postulated in 2002 by Ramot et al., and the 2011 innovation of pure complex fuzzy sets, proposed by Tamir et al.. In this paper we compare and contrast both forms of complex fuzzy set with type-2 fuzzy sets, as regards their rationales, ap...

Abstract: In this paper, a new hierarchical data-driven modelling strategy based on Interval Type-2 Fuzzy Clustering is elicited for the Interval Type-2 Takagi-Sugeno-Kang (TSK) Fuzzy Logic System. This framework which we have called the IT2-Squared framework uses interval type-2 fuzzy clustering for initial antecedent parameters and structures determination and least-squares algorithm for deri...

In this paper, we present a general framework for the study of interval type-2 rough fuzzy sets by using both constructive and axiomatic approaches. First, several concepts and properties of interval type-2 fuzzy sets are introduced. Then, a pair of lower and upper interval type-2 rough fuzzy approximation operators with respect to a crisp binary relation is proposed. Classical representations ...

Many problems arise in practical applications when data is extracted from a group of experts, all of whom do not collectively agree. The theory of Type 2 Fuzzy Multisets is capable of modelling these types of uncertainties in decision making. The purpose of this paper is to introduce the study of various algebraic structures of Type 2 Fuzzy Multisets. As a beginning of this study, the concept o...