Defuzzification method for a faster and more accurate control

Fuzzy control 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 a fuzzy control strategy since the imprecise data can he captured using linguistic variables in the rule-base. Fuzzy logic has certain disadvantages. The number of computations required for arriving at a certain output response for given inputs is very large and thus the system response is sluggish. Therefore to adapt fuzzy systems to real-time applications one needs to use faster algorithms and/or parallel processing. Also the process of defuzzification required to produce a single output value may lead to errors which can undo the advantages of fine control normally achievable using fuzzy logic. Special analytical techniques ensure that the complications of the defuzzification process are simplified; the method used retains the desirable 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.<<ETX>>