Fuzzy Logic was first introduced by Dr. Lotfi Asker Zadeh, a professor at University of California, Berkeley. “As the complexity of a system increases, it becomes more difficult and eventually impossible to make a precise statement about its behavior, eventually arriving at a point of complexity where the fuzzy logic method born in humans is the only way to get at the problem.” -Dr. Lotfi A. Zadeh To simply put it, Fuzzy Logic is a way to problem solve and analyze through a system which resembles human decisions, which can use approximate data to find precise information. Fuzzy logic is the way a system solves similar to Artificial Intelligence, however, the main difference is that Artificial Intelligence is trying to perform exactly like humans, while Fuzzy Logic will only perform similar to humans. The Fuzzy Logic Control-Analysis Method has three phases in order to make a decision. The first step is Input. During input, the system measures the condition of the assessment such as temperature, height, weight, or any type of date you are trying to measure. The second step, the system goes through the Processing phase in which the system processes the determined decision based on human determined “If X, then Y” rules. The third step is averaging, which averages the values of the “If X, then Y” rules in order to make a decision. When the Fuzzy Logic Control-Analysis Method comes to a decision, that is called the Output, which tells the system what to do. Example: the Fuzzy Logic’s “If X, then Y” rule to problem solve. -IF temperature IS very cold THEN stop fan -IF temperature IS cold THEN turn down fan -IF temperature IS normal THEN maintain level -IF temperature IS hot THEN speed up fan The system would have certain “fuzzy values” to determine and define very cold, cold, normal, and hot. Inside the system, it makes the decisions based on the value of each of these sets. The system would have values like: very cold < [64] F cold = [64, 68] F normal = [68,72] F hot > [72] F The system then measures the temperature and based on the values compared to what it measures, will make a decision to control the fan. Applications that uses Fuzzy Logic: • Automobile • Air conditioners • Cameras • Dishwashers • Elevators • Home appliances • Video game artificial intelligence • Language filters The application of Fuzzy logic is applied to our everyday use without us realizing it. A very good example of the application of fuzzy logic is automobiles. Most of us drive cars everyday. Automatic transmission cars uses fuzzy logic to determine which gear it needs to shift into based on the data of your speed and rpm. Cruise control is another application in our cars which uses fuzzy logic. When cruise control is set, the system recognizes the speed of the car and tries to keep it constant. When the car begins to slow down, the system tells the engine to work harder in order to maintain speed. The best way to see this is to set the cruise control to a certain speed, then go up hill. What I observe when I do this, the speed of my car begins to slow, the rpm goes up, working the engine, in order to give the car more acceleration to keep up with the set speed of the cruise control. Works Cited "Fuzzy logic." Wikipedia. 16 Jun 2009 <http://en.wikipedia.org/wiki/Fuzzy_logic>. "Chapter 1: Fuzzy Logic - a Powerful Way to Analyze and Control Complex Systems." FUZZY LOGIC FOR "JUST PLAIN FOLKS" . 16 Jun 2009 <http://www.fuzzy-logic.com/Ch1.htmiki/Fuzzy_logic>. Brule, James F. . "Fuzzy Systems - A Tutorial." austinlinks. 1985. 16 Jun 2009 <http://www.austinlinks.com/Fuzzy/tutorial.html>. "Fuzzy Logic." University of Florida. 16 Jun 2009 <http://www-pub.cise.ufl.edu/~ddd/cap6635/Fall-97/Short-papers/24.htm>. |

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