ABSTRACT
Since it was introduced by Zadeh in 1965, fuzzy logic has demonstrated to be an adequate tool for emulating the approximate reasoning mechanisms used by the human brain. Inference systems based on fuzzy logic share certain fea tures with other artificial intelligence paradigms. A fuzzy system acquires and represents its knowledge base symbolically, while knowledge is processed nu merically. The first feature permits the use of fast and simple mechanisms for representing and acquiring knowledge, structured in rules, and the second al lows the employment of fast numerical algorithms and the direct implementa tion of the system by a microelectronic circuit. The ability of fuzzy logic to describe a complex system by means of a simple and intuitive set of behavioral rules has motivated an increasing interest for applying it in fields such as in dustrial control, non-linear systems modeling, and decision-making systems.
