A Review Study of Fuzzy Controllers and Its Application in Decision Mapping

Abstract

Fuzzy logic is an approach to variable processing that allows for multiple possible truth values tobe processed through the same variable. Fuzzy logic attempts to solve problems with an open,imprecise spectrum of data and heuristics that makes it possible to obtain an array of accurateconclusions. The complexity of product design in industry has been continuously increasing.More factors are required to be considered simultaneously before a decision about the newproduct could be determined. For this reason, decision-making process costs much more timeanditmayevenbeimpossibletodeterminetheoptimaldecisionbynormalcalculations.Therefore, Fuzzy Inference System based on Fuzzy Logic is introduced as a quick decision-making tool to arrive at a good decision within much shorter time. This thesis focuses onstudying the features of membership functions in Mamdani-type fuzzy inference process. It isaimed at making the black box of fuzzy inference system to be transparent by adjusting themembership functions to control the relations between input and output variables. SystematictrialanderrorisimplementedbasedontheFuzzyLogicToolboxfromMATLAB,andconclusionsdevelopedfromexperimentshelpeliminatetheuncertaintiesofmembershipfunctions,sothattheinferenceprocessturnstobemore precise andreliable.