ABSTRACT
In this chapter, we describe some industrial applications of fuzzy control, neural control, neural-fuzzy control, and related neural-fuzzy technology. These examples are intended to give the reader some ideas about the type of problems that are appropriate for using the technology discussed in this text, about how to approach problems that arise in real-world situations, and how to evaluate the performance of the approach. These examples exemplify the need for soft computing approaches in decision-
making. They are intended to demonstrate the applicability of soft computing techniques, their strengths and weaknesses, and the need for evaluating various hybrid approaches. The Þrst two examples treat fuzzy control problems, and the last two examples describe neuro-fuzzy approaches to classiÞcation. There is no prescribed methodology or algorithm that dictates how problems can be solved. This provides a motivation to experiment with techniques that allow the combination of known variables in a manner that provides reasonable and realistic outcomes.
