ABSTRACT
This chapter discusses basic fuzzy logic (FL) concepts and their use for modeling, prediction, and control in drying. It provides fundamental principles of FL, as well as applications of FL in the form of FL models, FL controls, and adaptive neuro-fuzzy inference systems (ANFIS). FL is a computational technique developed by L. Zadeh to deal with uncertain or imprecise information, implicitly incorporated in any technical system or statement. FL is a further extension of the binary Boolean logic of "true" and "false", which is commonly used in the world of computers and other digital systems. Fuzzy logic and artificial neural networks (ANNs) are complementary technologies in the design of intelligent systems. The integration of these techniques in the form of ANFIS appears to be a promising tool for modeling, control, and optimization of complex systems with significant uncertainty. ANFIS architecture usually includes five layers: fuzzification layer; rule operation layer; normalization layer; consequent layer; and aggregation layer.
