Fuzzy Logic and Fuzzy Systems
Yi Chen, Yun Li · 2018
Fuzzy set theory, a generalisation of classical set theory, reflects the observation that the more complex a system becomes, the less meaningful are the low-level details in describing the overall system operation. Therefore the acquisition for precision in a complex system becomes a difficult task and often unnecessary. The main advantage of fuzzy set theory is that it excels in dealing with imprecision. With the development of computational intelligence, human inference-oriented fuzzy systems (FS) and fuzzy logic control (FLC) have received increasing attention world-wide. For example, a fuzzy controller incorporates uncertainty and abstract nature inherent in human decision-making into intelligent control systems. It tends to capture the approximate and qualitative boundary conditions of systems variables (as opposed to the probability theory that deals with random behaviour) by fuzzy sets with a membership function. Such a system flexibly implements functions in near human terms, i.e. IF-THEN linguistic rules, with reasoning by fuzzy logic, which is a rigorous mathematical discipline. Hence, it is termed a type of expert systems that handle problems widespread with ambiguity. It is well known for its capability in dealing with non-linear systems that are complex, ill-defined or time-varying.