Seminar Report on Fuzzy Logic
ABSTARCT
Fuzzy logic has rapidly become one of the most successful of today's technologies for developing sophisticated control systems. The reason for which is very simple. Fuzzy logic addresses such applications perfectly as it resembles human decision making with an ability to generate precise solutions from certain or approximate information. While other approaches require accurate equations to model real-world behaviors, fuzzy design can accommodate the ambiguities of real-world in human language and logic. Although genetic algorithms and neural networks can perform just as well as fuzzy logic in many cases, fuzzy logic has the advantage that the solution to the problem can be cast in terms that human operators can understand, so that their experience can be used in the design of the controller. This makes it easier to mechanize tasks that are already successfully performed by humans.
In a broad sense, fuzzy logic refers to fuzzy sets - a set with unsharp boundaries. Examples of fuzzy sets are “hot,” “tall,” “medium,” etc. In a narrow sense, fuzzy logic is a logical system that aims to formalize approximate reasoning .In fuzzy logic a fuzzy symbol can take any truth values from the closed set [0, 1] of real numbers thus generalizing the Boolean truth values. As the technology was further embraced, fuzzy logic was used in more useful applications.
In 1987, the first fuzzy logic-controlled subway was opened in Sendai in northern Japan. Here, fuzzy-logic controllers make subway journeys more comfortable with smooth braking and acceleration. Best of all, all the driver has to do is push the start button! Fuzzy logic was also put to work in elevators to reduce waiting time. Since then, the applications of Fuzzy Logic technology have virtually exploded, affecting things we use everyday, for example, the fuzzy washing machine. A load of clothes in it and press start, and the machine begins to churn, automatically choosing the best cycle.
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Fuzzy logic has rapidly become one of the most successful of today's technologies for developing sophisticated control systems. The reason for which is very simple. Fuzzy logic addresses such applications perfectly as it resembles human decision making with an ability to generate precise solutions from certain or approximate information. While other approaches require accurate equations to model real-world behaviors, fuzzy design can accommodate the ambiguities of real-world in human language and logic. Although genetic algorithms and neural networks can perform just as well as fuzzy logic in many cases, fuzzy logic has the advantage that the solution to the problem can be cast in terms that human operators can understand, so that their experience can be used in the design of the controller. This makes it easier to mechanize tasks that are already successfully performed by humans.
In a broad sense, fuzzy logic refers to fuzzy sets - a set with unsharp boundaries. Examples of fuzzy sets are “hot,” “tall,” “medium,” etc. In a narrow sense, fuzzy logic is a logical system that aims to formalize approximate reasoning .In fuzzy logic a fuzzy symbol can take any truth values from the closed set [0, 1] of real numbers thus generalizing the Boolean truth values. As the technology was further embraced, fuzzy logic was used in more useful applications.
In 1987, the first fuzzy logic-controlled subway was opened in Sendai in northern Japan. Here, fuzzy-logic controllers make subway journeys more comfortable with smooth braking and acceleration. Best of all, all the driver has to do is push the start button! Fuzzy logic was also put to work in elevators to reduce waiting time. Since then, the applications of Fuzzy Logic technology have virtually exploded, affecting things we use everyday, for example, the fuzzy washing machine. A load of clothes in it and press start, and the machine begins to churn, automatically choosing the best cycle.
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