Industrial Applications Of Fuzzy Technology

The 1980s saw a whole wave of practical applications of fuzzy theory, mainly in the field of process control, with Japan as pioneer. In the '90s there has been a flood of applications to household electrical appliances, and?fuzzy? has become a high-tech buzz-word in Japan. Since then many countries have followed suit and developed their own fuzzy applications.This book reviews the burgeoning industrial applications of fuzzy theory. The contributors are mostly industrial engineers or research experts in the field. The areas covered include automobiles, home appliances, voice recognition, medical techniques, fuzzy design, process control, space operations and mobile autonomous robots.Very recently the development of fuzzy theory has become intertwined with fields such as neural networks and chaos. This volume also summarizes such trends in an industrial context.The book will be of use to senior undergraduates or graduate students, industrial research scientists, and anyone interested in the wide-ranging applicational aspects of fuzzy theory today.

The application of fuzzy technology is widely known as a technological revolution. Shortly after it appeared, its value has rapidly become appreciated. It is absolutely indispensable for introducing the latest developments not only domestically but also internationally. This book is arranged to introduce easy to understand explanations mainly centered on concrete applications. It consists of twelve chapters in total which are all independently readable and provide different approaches on various projects. The minimum of Fuzzy Theory that is needed to understand its practical applications is given in Chapter 1. Chapters 2 to 5 discuss hardware, including chips, and software tools used in constructing system. Chapters 6 to 12 cover a series of practical applications. These in clude applications for industrial processes and plants, transportation systems, which were among the first applications, and applications for consumer products such as household electrical appliances. These elements together finally produced the worldwide "Fuzzy Boom". This book can be read by a wide variety of people, from undergraduate and graduate students in universities to practical engineers and project managers working in plants. The information contained in this book is a first step to this field of interest.

This book introduces a dynamic, on-line fuzzy inference system. In this system membership functions and control rules are not determined until the system is applied and each output of its lookup table is calculated based on current inputs. The book describes the real-world uses of new fuzzy techniques to simplify readers’ tuning processes and enhance the performance of their control systems. It further contains application examples.

Introduction to fuzzy logic control. History of industrial applications of fuzzy logic in Japan. Fuzzy logic applications at OMRON Corporation. Survey of fuzzy logic applications in image-processing equipment. Applications of neural networks and fuzzy logic to consumer products. Knowledge processing based on fuzzy associative memory and its application to a helicopter control. Fuzzy logic hierarchical controller for a recuperative turboshaft engine: from mode selection to mode melding. Progress in reseacrh on autonomous vehicle motion planning. Autonomous navigation of a mobile robot using the behaviorist theory and VLSI fuzzy inferencing chips. Artificial intelligence, fuzzy logic, and sensor clusters. Intelligent sensor systems for space operations. Two automated tuning methods for fuzzy logic-based process control. On fuzzy control of nonchlorofluorocarbon air-conditioning systems. Fuzzy logic applications in Europe. Software tools for fuzzy control.

Fuzzy Logic Foundations and Industrial Applications is an organized edited collection of contributed chapters covering basic fuzzy logic theory, fuzzy linear programming, and applications. Special emphasis has been given to coverage of recent research results, and to industrial applications of fuzzy logic. The chapters are new works that have been written exclusively for this book by many of the leading and prominent researchers (such as Ronald Yager, Ellen Hisdal, Etienne Kerre, and others) in this field. The contributions are original and each chapter is self-contained. The authors have been careful to indicate direct links between fuzzy set theory and its industrial applications. Fuzzy Logic Foundations and Industrial Applications is an invaluable work that provides researchers and industrial engineers with up-to-date coverage of new results on fuzzy logic and relates these results to their industrial use.

This volume focuses on the practical applications of fuzzy control, which is one of the most promising research fields in fuzzy engineering. Control engineers in many fields can benefit from these case studies, which include the control of trains, aircraft, robots, and various industrial processes. Also featured is a comprehensive ''Annotated Bibliography of Fuzzy Control''.

Fuzzy Control of Industrial Systems: Theory and Applications presents the basic theoretical framework of crisp and fuzzy set theory, relating these concepts to control engineering based on the analogy between the Laplace transfer function of linear systems and the fuzzy relation of a nonlinear fuzzy system. Included are generic aspects of fuzzy systems with an emphasis on the many degrees of freedom and its practical design implications, modeling and systems identification techniques based on fuzzy rules, parametrized rules and relational equations, and the principles of adaptive fuzzy and neurofuzzy systems. Practical design aspects of fuzzy controllers are covered by the detailed treatment of fuzzy and neurofuzzy software design tools with an emphasis on iterative fuzzy tuning, while novel stability limit testing methods and the definition and practical examples of the new concept of collaborative control systems are also given. In addition, case studies of successful applications in industrial automation, process control, electric power technology, electric traction, traffic engineering, wastewater treatment, manufacturing, mineral processing and automotive engineering are also presented, in order to assist industrial control systems engineers in recognizing situations when fuzzy and neurofuzzy would offer certain advantages over traditional methods, particularly in controlling highly nonlinear and time-variant plants and processes.