Defuzzification is the process of converting the degrees of membership of output linguistic variables within their linguistic terms into crisp numerical values. Consider the following rules:

(1) IF Vehicle Position x is Center (degree of membership = 0.8) AND (Minimum) Vehicle Orientation β is Left Up (degree of membership = 1.0) = 0.8
THEN Steering Angle φ is Negative Small
(2) IF Vehicle Position x is Right Center (degree of membership = 0.1) AND (Minimum) Vehicle Orientation β is Left Up (degree of membership = 1.0) = 0.1
THEN Steering Angle φ is Negative Medium

These two rules specify two non-zero values for the Steering Angle φ output linguistic variable:

Negative Medium Negative Small to a degree of to a degree of 0.1 0.8
Remarque Fuzzy controllers use an implication method to scale the membership functions of output linguistic variables before performing defuzzification.

A fuzzy controller can use one of several mathematical methods to perform defuzzification: Center of Area (CoA), modified Center of Area (mCoA), Center of Sums (CoS), Center of Maximum (CoM), or Mean of Maximum (MoM). Selecting a defuzzification method depends on the context of the design you want to calculate with the fuzzy controller.

Related Information

Center of Area (CoA)

Modified Center of Area (mCoA)

Center of Maximum (CoM)

Mean of Maximum (MoM)

Center of Sums (CoS)

Selecting a Defuzzification Method