Fuzzy Reasoning in Information, Decision and Control Systems

This book is devoted to the study of fuzzy reasoning as applied to decision-making and control processes. It contains a collection of contributions covering a wide range of topics within the field. It contains 21 papers, written by 34 contributors and is divided into five parts. Part 1 involves four chapters providing background material together with useful techniques for the validation of fuzzy knowledge bases and the software representation of fuzzy sets and fuzzy logic. Part 2 presents an overview of neuro-fuzzy expert systems along with an important case study, and a neural network model which is suitable for fuzzy reasoning. Part 3 presents the state of the art of fuzzy controllers, including design and implementation aspects. This part starts with a chapter on the demystification of fuzzy control and includes critical evaluations of fuzzy controllers, along with new types of fuzzy controllers such as the sliding mode fuzzy controller.Part 4 involves a chapter on fuzzy parameter and state estimation, which is of fundamental importance in a variety of applications, a chapter on fuzzy reasoning as used in rule-based systems, and a chapter on computing the multivariable shape of an n-D pattern class. Finally, Part 5 presents six important applications dealing with industrial robotic systems, mechanical systems, manipulators with artificial rubber muscles, Petri nets, biomedical engineering, and non-destructive fruit collection. The book is suitable for researchers and practitioners, as well as for teachers and students in related master and doctoral courses.