The following picture details the three ways to depict the transformation from fuzzy logic to crisp logic. The processual representation (the flowchart in the middle) shows the positive feedback loop that the fuzzy logic controller uses to make the dataset crisp ("p.c." in the chart stands for "position controller").
The algorithm, shown leftmost, delineates the logical statements that constitute the following flowchart. The purpose of the positive feedback loop is served by the nested if-then clusters that, going by the graphics on the first row, ensure that intuitive conclusions (as represented by the fuzzy set) are brought as close to the real thing (as represented by the crisp set) as possible using statistical data. The equation on the rightmost determines the mathematical convergence, i.e., the minimum number of line segments that would have to be perfectly aligned for any following segments to just fall in place after them (ref: German tank problem).
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