ABSTRACT
This chapter demonstrate how fuzzy logic can be used for system modeling. It discusses both kinds of models and how they apply to dynamics systems. The chapter also discusses single input single output system models. A paradigm shift from classical thinking to fuzzy thinking was initiated by the concept of fuzzy sets and the idea of mathematics based on fuzzy sets. It emerged from the need to bridge the gap between mathematical models and their interpretations. This gap has become increasingly disturbing, especially in the areas of biology, cognitive sciences, and social and applied sciences, such as modern technology and medicine. In fuzzy logic, the transition is gradual and not abrupt, from member to nonmember. It can deal with uncertainty in terms of imprecision, nonspecificity, vagueness, and inconsistency. Fuzzy sets were specifically designed to mathematically represent uncertainty and vagueness, and to provide formalized tools for dealing with imprecision intrinsic to many problems.
