Preface

Intelligent control, which is defined as a combination of control theory, operations research, and artificial intelligence (AI) is emerging as one of the most popular new technologies in the industrial and manufacturing worlds. Among many possible new technologies based on AI, fuzzy logic is now perhaps the most popular area, judging by the billions of dollars worth of sales and close to 2000 patents issued in Japan alone since the announcement of the first fuzzy chips in 1987. Thanks to tremendous technological and commercial advances in fuzzy logic in Japan and other nations, today fuzzy logic is enjoying an unprecedented popularity in the technological and engineering fields including manufacturing. Fuzzy logic technology is now being used in numerous consumer and electronic products and systems, even in the stock market and medical diagnostics. The most important issue facing many industrialized nations in the next several decades will be global competition to an extent that has never before been posed. The arms race is diminishing and the economic race is in full swing. Fuzzy logic is but one such front for global technological, economical, and manufacturing competitions. An equally or perhaps much more important aspect of this new surge of interest in fuzzy logic is the educational aspect of fuzzy logic and fuzzy logic applications, including control systems. In 1989, in a study performed for the U.S. Congress, the United States Office of Technology Assessment studied more than 12 competing technologies for cost reduction in space applications. The number-one technology on their list turned out to be “expert systems,” including “fuzzy expert systems.”

The purpose of this book is to describe one experience in the education of engineering students at the University of New Mexico over a span of two years. First, the book provides some basic concepts of fuzzy set theory (Chapter 2), fuzzy logic (Chapter 3), fuzzy control (Chapters 3 and 4), and fuzzy logic software and hardware (Chapter 6). The softwares presented are Togai’s Fuzzy-C Systems, NeuraLogix’s NLX-230 Fuzzy Microcontroller, Bell Helicopter Textron’s FULDEK, and University of New Mexico’s FLCG. The reader may send in a postcard (found at the end of the book) to obtain further information on the latter two software packages. A number of actual software and hardware applications of fuzzy logic follow Chapter 6 as case studies in separate chapters (Chapters 7-18). The areas of application in the book are:

The reader may access the technical papers through an organized table of contents as well as the subject index at the end of the book. A list of all contributors is also available for easy access by readers of this volume.

The editors take this opportunity to thank Professor Lotfi Zadeh for his constant source of inspiration and encouragement. We thank all the authors for their contributions to fuzzy logic, to its applications, and to this volume. We also express our gratitude to Dean James Thompson, College of Engineering, Professor Nasir Ahmed, Chair, Electrical and Computer Engineering Department, and Professor Jerry Hall, Chair, Civil Engineering Department, all of the University of New Mexico, for supporting our efforts.

Our most sincere thanks and appreciation must go to Ms. Nancy Gillan of UNM’s CAD Laboratory for Intelligent and Robotic Systems for her diligent and superb work in typesetting, copyediting, and preparing the manuscript for Prentice Hall Publishers. Last, but by no means least, we sincerely and thoughtfully thank our families for their understanding and sacrifice during the writing and assembling of this volume.

Mohammad Jamshidi

Nader Vadiee

Timothy J. Ross