The Fuzzy Analytic Network Process (ANP) is generally used for solving multicriteria decision making (MCDM) problems by considering the pairwise comparison between criteria/sub-criteria, and inner/outer dependencies among criteria. Linguistic expressions are used for experts’ judgements, and these judgements are imprecise and vague. Hence, incorporating fuzziness with multi-criteria decision ma...

In this paper, an interval Type-2 fuzzy logic based pitch angle controller is proposed for fixed speed wind energy system (WES) to maintain the aerodynamic power at its rated value. The pitch angle reference is generated by the proposed controller which can compensate the non-linear characteristics of the pitch angle to the wind speed. The presence of third dimension in the Type-2 fuzzy logic c...

An innovative adaptive control method for speed control of induction motor based on field oriented control is presented in this paper. The fusion of sliding-mode and type-2 neuro fuzzy systems is used to control this system. An online learning algorithm based on sliding-mode training algorithm, and type-2 fuzzy systems is employed to deal with parametric uncertainties and disturbances, by adjus...

Abstract The fuzzy transform setting (F-transform) is proposed as a tool for representation and approximation of type-1 and type-2 fuzzy numbers; the inverse F-transform on appropriate fuzzy partition of the membership interval [0,1] is used to characterize spaces of fuzzy numbers in such a way that arithmetic operations are de…ned and expressed in terms of the F-transform of the results. A typ...

osting by E Abstract Direct adaptive fuzzy controller is a class of adaptive fuzzy controllers which use fuzzy logic system (FLS) as controller. Interval type-2 fuzzy sets are able to model and minimize the numerical and linguistic uncertainties associated with the inputs and outputs of fuzzy logic controller (FLC). In this paper, a direct adaptive interval type-2 FLC is proposed for controllin...

This paper presents a type-2 fuzzy rule based expert system to handle uncertainty in complex problems such as portfolio selection. In a type-2 fuzzy expert system both antecedent and consequent have type-2 membership function. This research uses indirect approach fuzzy modeling, where the rules are extracted automatically by implementing a clustering approach. For this purpose, a new cluster an...

Traditional fuzzy logic systems are unable to handle the uncertainties of real-world applications. By "handle" I mean directly model and minimize the effect of. In this talk I will explain rule-based type-2 fuzzy logic systems and how they can handle a broad range of uncertainties totally within their framework. This is accomplished by adding a new mathematical dimension-a third dimension-to ty...

The Interval Type-2 Fuzzy Logic Controller (IT2FLC) for a Quadruple Tank Process (QTP) is demonstrated in this paper. Here the Interval Type-2 based Fuzzy membership function is used. The QTP is made to operate in minimum phase mode. The vertices of fuzzy membership functions are tuned with IT2FLC to minimize Integral Absolute Error. Performance of IT2FLC and Type-1 Fuzzy Logic Controller (T1FL...