Abstract—In fuzzy control systems, fuzzification and defuzzification are two important procedures. Defuzzification plays an important part in the implementation of a fuzzy system, since the fuzzy data is not suitable for real time applications; it needs to be converted into crisp data. This paper proposes a novel VLSI architecture of a weighted average method (WAM) defuzzification method. The W...

In this paper, design and analysis of a novel current-mode defuzzification circuit is presented. The proposed defuzzification circuit is based on current-mode four-quadrant multipliers that have been constructed with simple current squarer and current differencing buffered amplifier (CDBA). This circuit has capable of high linearity, simple structure, and wide input current range. The defuzzifi...

This paper deals with the simplest fuzzy PI controllers under various defuzzification methods. The various simplest fuzzy PI controllers consist of two triangular input fuzzy sets and three triangular output fuzzy sets on the universe of discourse of input and output variables, respectively, linear control rules, intersection T-norm, Lukasiewicz and Zadeh OR T-conorms, and any valid inference m...

The problem of defuzzification is examined in this study from a broader perspective as a special way of dealing with the general problem of retranslation. The study includes an overview of different formulations of the problem of defuzzification, as well as an overview of methods that have been suggested in the literature to deal with the problem. Our own approach to defuzzification, which is d...

Decision-Making Trial and Evaluation Laboratory (DEMATEL) method is widely used in many real applications. With the desirable property of efficient handling with the uncertain information in decision making, the fuzzy DEMATEL is heavily studied. Recently, Dytczak and Ginda suggested to defuzzify the fuzzy numbers firstly and then use the classical DEMATEL to obtain the final result. In this sho...

TYPE-2 fuzzy sets (T2 FSs), originally introduced by Zadeh [3], provide additional design degrees of freedom in Mamdani and TSK fuzzy logic systems (FLSs), which can be very useful when such systems are used in situations where lots of uncertainties are present [4]. The implementation of this type-2 FLS involves the operations of fuzzification, inference,and output processing. We focus on ―outp...

This paper is concerned with the defuzzification of the discretised generalised type-2 fuzzy set. In 2008 Liu proposed the α-Plane Representation — a decomposition of the generalised type-2 set into horizontal slices termed ‘α-planes’. An α-plane is akin to an interval type-2 fuzzy set. The α-Plane Representation must be used in conjunction with an interval defuzzification method: The three mai...

Abstract Stratification is a feature of the type-reduced set general type-2 fuzzy set, from which new technique for defuzzification, Stratic Defuzzification, may be derived. Existing defuzzification strategies are summarised. The stratified structure described, after Defuzzifier presented and contrasted experimentally accuracy efficiency with both Exhaustive Method Defuzzification (to benchmark...

Computing the output of fuzzy systems usually passes through three stages i.e. fuzzification, inference, and defuzzification. The computation of the output requires too many operations and considerable time. This apparently discourages the use of fuzzy systems in time-critical applications. In this paper, a new two-stage representation of fuzzy systems, which reduces the operations needed to co...

Many ranking methods have been proposed so far. The fuzzy number defuzzification method with continuous weighted quasi-arithmetic means was proposed by Yoshida in the domain (−∞,+∞) . Recently in [22], the researcher used this method with the ordinary fuzzy set in a compact interval, that all the conclusions can be extended to the ordinary fuzzy set in [24] directly. This parameterized defuzzif...