Defuzzification Method for a Faster and More Accurate Control

Fuzzy logic is achieved by formulating a rule base which is based on experience gathered by human operators. Those systems which cannot be modeled mathematically benefit most from Fuzzy control strategy since the imprecise data can be captured by using linguistic data in the rule-base. Fuzzy logic has certain disadvantages. The number of computations required for arriving at a certain output for a given input is very large and thus the system response is sluggish. Therefore to adapt Fuzzy systems to real time applications we need to use faster algorithms and/or parallel processing. Also the process of defuzzification required to produce single output may lead to errors which can undo the advantages of fine control normally achievable by Fuzzy logic. Special analytical techniques ensure that the complications of the defuzzification process are simplified; the method used retains the desired features of fuzzy control. This paper aims to present a comparison between the conventional fuzzy controller and a fuzzy logic controller based on the techniques mentioned above.