ABSTRACT
The concepts of soft computing that we introduced in Chapter 1 form the guiding principles of fuzzy logic. With fuzzy logic, the system is made to give the most probable output to any kind of input based on the predefined rules. Fuzzy systems are a modified form of rule-based approach, in which rules are applied to find the output of any input. In place of strict rules applied over the classes or sets, however, the rules are much softer in the manner in which they are applied. This not only gives a scope for the function to perform well in the presence of uncertainties and noise, but it also makes it possible to obtain more realistic systems that imitate natural behavior. Fuzzy systems are used in numerous real life industrial applications, including biomedical engineering and robotic control. The success of fuzzy systems in such varied domains clearly speaks to the effectiveness of these systems, which form an integral part of soft computing. Fuzzy logic is the natural choice when modeling systems that have predefined rules governing their behavior.
