Fuzzy Logic Basics

Allen Bonde
GTE Government Systems Corp.
Needham, MA 02194
abonde@gte.com

Fuzzy Logic is a departure from classical two-valued sets and logic, that uses "soft" linguistic (e.g. large, hot, tall) system variables and a continuous range of truth values in the interval [0,1], rather than strict binary (True or False) decisions and assignments.

Formally, fuzzy logic is a structured, model-free estimator that approximates a function through linguistic input/output associations.

Fuzzy rule-based systems apply these methods to solve many types of "real-world" problems, especially where a system is difficult to model, is controlled by a human operator or expert, or where ambiguity or vagueness is common. A typical fuzzy system consists of a rule base, membership functions, and an inference procedure (see Figure).

Some Fuzzy Logic APPLICATIONS include:

The key BENEFITS of fuzzy design are:

For More Information:

Good overview articles:

Classic Papers:

Excellent Books:

Journals that cover fuzzy logic:

   ________________     _______________     ________________
I  |               |    |              |    |               | O
N  |Crisp-to-Fuzzy |    |  Inference   |    |Fuzzy-to-Crisp | U
P  |               |--->|              |--->|               | T
U  |    FUZZIFY    |    | max-min, etc |    |   DEFUZZIFY   | P
T  |_______________|    |______________|    |_______________| U
                                                              T
  membership functions     rule base          max, average,
                                              centroid,
                                              singleton, etc