This book addresses the modeling of complex, nonlinear, or partially unknown systems by means of techniques based on fuzzy set theory and fuzzy logic. The author focuses on the development of transparent, rule-based fuzzy models that can accurately predict the quantities of interest and at the same time provide insight into the system that generated the data. Topics covered include the selection of appropriate model structures, the acquisition of dynamic fuzzy models from process measurements, and the design of nonlinear controllers based on fuzzy models. The main features of the presented techniques are illustrated by simple examples. In addition, three real-world applications are described.