Method of reasoning that resembles human reasoning

This approach is similar to how humans perform decision making and it involves all intermediate possibilities between Yes and No.

Why use Fuzzy Logic?

• it controls machines and consumer products
• if not accurate reasoning, it at least provides acceptable reasoning
• helps in dealing with the uncertainty in engineering

Architecture of Fuzzy Logic

Rules: contains all the rules and the if-then conditions offered as input to control the decision making system

Fuzzifier: fuzzification takes place here. Convert the crisp input into a fuzzy set. Splits

Intelligence: inference engine. Computes the degree of matching between the fuzzy set and the rules. Combines the fuzzy input and the rules to form the control action, thus obtaining the fuzzy output set.

Defuzzifier: defuzzification takes place here. It converts the fuzzy output set into a crisp output

Membership function

graph that defines how each point in the input space is mapped to membership values between 0 and 1.

It allows you to qualify linguistic terms and represent a fuzzy set graphically