Fuzzy Logic

INTRODUCTION:

FUZZY LOGIC

Automatic control has played role in the advance of engineering and science. In addition to its extreme importance in robotic systems, and the same, automatic control has become an important and integral part of modern manufacturing and industrial processes. Automatic control is essential in such industrial operations as controlling pressure, temperature, humidity, viscosity, and flow in the process industries.

While modern control theory has been easy to practice (Ogata, 2008), FLC has been rapidly gaining popularity among practicing engineers. This increased popularity can be attributed to the fact that fuzzy logic provides a powerful vehicle that allows engineers to incorporate human reasoning in the control algorithm.

The designed controller used fuzzy logic control (FLC) implements human reasoning that been programmed into fuzzy logic language. In FLC, the dynamic behavior of a fuzzy system is characterized by a set of linguistic description rule based on expert knowledge. The expert knowledge is usually of the form:

IF (a set of conditions are satisfied, associated with fuzzy concepts or linguistic terms), THEN (a set of consequences can be inferred).

The idea of fuzzy sets is due to Dr. Lotfi A. Zadeh, who introduced a function that expressed the degree of belonging to a given set as a function taking values in the range 0 to 1 (Shancez et. al., 1997).



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