Easy Way to Understand Fuzzification in Fuzzy Logic System

Fuzzification is a process to convert numerical values (real values) of variable inputs into Linguistic values (Fuzzy values). Fuzzy values have value range “0” to “1” where “0” is minimum value and “1” is maximum value. There are 2 input variables i.e. Angle and Distance in the container crane controller as shown in the figure below.

Input variable Angle has 5 membership functions (linguistic variables); neg_big, neg_small, zero, pos_small & pos_big, while input variable Distance also has 5 membership functions; neg_close, zero, close, medium & far. In addition, output variable Power has 5 membership functions i.e. pos_high, pos_medium, zero, neg_medium and neg_high.

Based on input variable Angle in the figure above, Angle with real value 4° has 2 linguistic values i.e. zero (0.2) and pos_small (0.8). And input variable Distance with real value 12 m also has 2 linguistic variables; medium (0.9) and far (0.1).

Fuzzification of Input Variables:

1. Angle (4°) has 2 membership functions:

• zero = 0.2
• pos_small = 0.8

2. Distance (12 m) has 2 membership functions:

• medium = 0.9
• far = 0.1
  
  

Source of figures: Industrial Application of Fuzzy Logic Control (slide presentations), Inform Software Corporation, 20001 Midwest Rd., Oak Brook, IL 60521, U. S. A.