An ordinary or computer-driven thermostat would require you to specify at exactly what temperature the fan should turn off. The thermostat would then measure the current temperature, and if it were above the specified temperature, it would turn on the fan at full blast until the desired temperature was reached. This is not very efficient, especially when compared with a fuzzy controller. Using a fuzzy logic controller, you could specify a range of temperatures that would be considered cold, cool, comfortable, warm, and hot. The fuzzy rules would control fan speed based on temperature range.
Fuzzy logic has certain advantages over traditional logical systems.
Fuzzy logic systems are, for the most part, easy to set up and use. The primary difficulty in using fuzzy logic is that the programmer must first thoroughly understand the intracacies of and be able to precisely define a problem, and then must be able to evaluate and fine-tune the results. Critics of fuzzy logic systems in fact contend that these systems, in part because they are not entirely analytic and thus involve fine-tuning, are unstable. Nonetheless, developments in neural networks may someday remedy this problem by enabling a computer to learn how to define the problem, set up rules, and perform any necessary fine-tuning itself. Fuzzy goings-on at Duke Paul Wang, Ph.D., is a professor of electrical engineering at Duke and one of the world's foremost fuzzy logicians.