This paper proposes an optimal design for interval type-2 Takagi-Sugeno-Kang (TSK) fuzzy logic system. In this method, the fuzzy c-means clustering algorithm is used to determine structure of fuzzy rule as well as number of rules. A hybrid between chaos firefly algorithm and genetic algorithms (CFGA) is developed, which is used to find the desirable parameters of membership functions and conseq...

In thispaper a reviewof type-2 fuzzy logic applications inpattern recognition, classificationandclustering problems is presented. Recently, type-2 fuzzy logic has gained popularity in a wide range of applications due to its ability tohandle higher degrees of uncertainty. In particular, therehavebeen recent applications of type-2 fuzzy logic in the fields of pattern recognition, classification a...

This paper presents research on applications of fuzzy logic and higher-order fuzzy logic systems to control filters reducing air pollution [1]. The filters use Selective Catalytic Reduction (SCR) method and, as for now, this process is controlled manually by a human expert. The goal of the research is to control an SCR system responsible for emission of nitrogen oxide (NO) and nitrogen dioxide ...

in this paper we continue development of formal theory of a special class offuzzy logics, called eq-logics. unlike fuzzy logics being extensions of themtl-logic in which the basic connective is implication, the basic connective ineq-logics is equivalence. therefore, a new algebra of truth values calledeq-algebra was developed. this is a lower semilattice with top element endowed with two binary...

Abstract: This paper presents a new general type-2 fuzzy logic method for edge detection applied to color format images. The proposed algorithm combines the methodology based on the image gradients and general type-2 fuzzy logic theory to provide a powerful edge detection method. General type-2 fuzzy inference systems are approximated using the α-planes approach. The edge detection method is te...

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...

Two advanced controllers were developed in this paper, i.e., a type-1 and a type-2 fuzzy logic controller and their performances compared in simulation for a case study, i.e., a binary distillation column, which is characterized by high nonlinearities and parameter uncertainties in the underlying mathematical model. Priority was given to the type-2 fuzzy controller, with special attention to in...

Planning resources for a supply chain is a major factor determining its success or failure. In this paper we introduce an Interval Type-2 Fuzzy Logic model of a distribution network. It is believed that the additional degree of uncertainty provided by Interval Type-2 Fuzzy Logic will allow for better representation of the uncertainty and vagueness present in resource planning models. First, the...

In this paper we address lhe issues brought by Elkan in his article, "The Paradoxical Success of Fuzzy Logic" [3]. Elkan's work has caused concem since purportedly reveals a Fuzzy Logic weakness regarding its theoretical foundations. A further investigation of Elkan's theorem ("theorem 1") revealed that its conclusion is not correct. Afier indicating lhe points where we disagree with Elkan, we ...