Fuzzy Control Systems

Abstract

Fuzzy control has been an active research and application area of intelligent controls for the past twenty years. As we have mentioned in Section 1.2.2, fuzzy sets were first proposed by Zadeh [49] as a method of handling real world classes of objects. Since then, a great amount of research efforts has been carried out both in the theoretical investigations and practical applications of fuzzy sets and fuzzy control.Fuzzy control is a kind of control approach that uses the fuzzy set theory. The usefulness of fuzzy control can be considered in two respects. On one hand, fiizzy control offers a novel mechanism to implement such control laws that are often knowledge-based (rule-based) or even in linguistic description. On the other hand, fuzzy control provides an alternative methodology to facilitate the design of nonlinear controllers for such plants being controlled, that are usually uncertain and very difficult to cope with by using conventional nonlinear control theory.Expert Control Systems and Fuzzy Logic Control (FLC) systems have certainly one thing in common: both aim to model human experience, human decision-making behavior. There are, however, clear differences between expert control systems and fuzzy logic control systems: (1) The existing FLC systems originated in control engineering rather than in Artificial Intelligence; (2)~FLC models are mostly rule-based systems; (3) The application domains of FLC are narrower than those of expert control systems; (4) The rules of FLC systems are generally not extracted from the human expert through the system but formulated explicitly by the FLC designer. For these reasons, it is necessary to discuss the fiizzy control system separately from the expert control systems in this chapter.In this section, the foundation of fuzzy set and fiizzy logic for control is briefly reviewed at first, then the types, structure, design and properties of fuzzy logic controller are presented, and an application example of FLC is demonstrated at last.