4 edition of Industrial applications of fuzzy control found in the catalog.
by North-Holland, Sole distributors for the U.S.A. and Canada, Elsevier Science Pub. Co. in Amsterdam, New York, New York, N.Y., U.S.A
Written in English
|Other titles||Fuzzy control.|
|Statement||edited by Michio Sugeno.|
|Contributions||Sugeno, Michio, 1940-|
|LC Classifications||TJ213.7 .I47 1985|
|The Physical Object|
|Pagination||viii, 269 p. :|
|Number of Pages||269|
|LC Control Number||85015908|
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. Currently there are many applications of Fuzzy Logic utilized by common household devices, products which most people are familiar with. The benefit of a Fuzzy Logic controller becomes transparent to the user of consumer devices since the Fuzzy Module or function is embedded within the product.
Fuzzy logic is an extension of Boolean logic by Lot Zadeh in based on the mathematical theory of fuzzy sets, which is a generalization of the classical set theory. By introducing the notion of degree in the veri cation of a condition, thus enabling a condition to be in a state other than true or false, fuzzy logic provides a very valuable. A major real-life application was Sendai’s fuzzy logic control system which began to operate in and was and is a striking success. In the realm of medical instrumentation, a notable real-life application is Omron’s fuzzy- logic-based and widely used blood pressure meter.
The book is a collection of new interesting industrial applications introduced by several research groups and industrial partners. It describes the principles and results of industrial applications of Soft Computing methods and introduces new possibilities to gain technical and economic benefits by using this methodology. Abstract: This paper describes an application of fuzzy logic in designing controllers for industrial plants. A fuzzy logic is used to synthesize linguistic control protocol of a skilled operator. The method has been applied to pilot scale plants as well as in practical situations.
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out of 5 stars Industrial Applications of Fuzzy Control, by M. Sugeno. Reviewed in the United States on Febru I recomend it to control engineers who can apply many theorical & experimental applications on Cited by: Jana D, Pramanik S, Sahoo P and Mukherjee A () Interval type-2 fuzzy logic and its application to occupational safety risk performance in industries, Soft Computing - A Fusion of Foundations, Methodologies and Applications,(), Online publication date: 1.
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''. A Microprocessor Based Fuzzy Controller for Industrial Purposes (T. Yamazaki, M. Sugeno). The Application of Fuzzy and Artificial Intelligence Methods in the Building of a Blast Furnace Smelting Process Model (H. Zhao, M.
Ma). An Annotated Bibliography of Fuzzy Control (R.M. Tong). Other Titles: Fuzzy control: Responsibility: edited by Michio.
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.
A detailed description is given of two rotary cement kiln control projects, which resulted in one of the first successful test runs on a full scale industrial process. It is concluded that further investigations are required with respect to the applicability of structural programming, and stability problems in fuzzy control by: Other industrial applications of fuzzy model-based predictive control are reported in,.
Conclusions. The paper addresses a brief survey on industrial applications of fuzzy control. The following classification of the control systems has been proposed with this regard: Cited by: Much work on fuzzy control, covering research, development and applications, has been developed in Europe since the 90's.
Nevertheless, the existing books in the field are compilations of articles without interconnection or logical structure or. 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 t. to automatic control,” Proc. IFAC Stochastic Control Symp, Budapest, FLC provides a nonanalytic alternative to the classical analytic control theory. application today is in a realm not anticipated when fuzzy logic was conceived, namely, the realm of fuzzy-logic-based.
A fuzzy control system is a control system based on fuzzy logic—a mathematical system that analyzes analog input values in terms of logical variables that take on continuous values between 0 and 1, in contrast to classical or digital logic, which operates on discrete values of either 1 or 0 (true or false, respectively).
Professor Yurkovich's research has focused on the theory and applications of control technology, in the areas of system identification and parameter set estimation for control, and fuzzy logic for control, in application areas including flexible mechanical structures, industrial control systems, and automotive systems/5(2).
Advanced Fuzzy Logic Technologies in Industrial Applications addresses the problem by introducing 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.
Fuzzy Control Systems explores one of the most active areas of research involving fuzzy set theory. The contributors address basic issues concerning the analysis, design, and application of fuzzy control systems.
Divided into three parts, the book first devotes itself to the general theory of fuzzy control systems. The industrial applications of fuzzy control are characterized by the use of heuristic rules that can be a viable alternative to classical crisp (non-fuzzy) control for the control of ill-defined.
for control problems—attractive applications (mainly in automation and industrial control) led to a “fuzzy boom” especially in Europe in the early s. These Only very few successful application of fuzzy model-based control are reported.
Abstract: The theory and the applications of artificial neural networks, especially in a control field, are described. Recurrent networks and feedforward networks are discussed. Application to pattern recognition, information processing, design, planning, diagnosis, and control. The emergence of fuzzy logic and its applications has dramatically changed the face of industrial control engineering.
Over the last two decades, fuzzy logic has allowed control engineers to meet and overcome the challenges of developing effective controllers for increasingly complex systems with poorly defined dynamics. Motion control is widely used in all types of industries including packaging, assembly, textile, paper, printing, food processing, wood products, machinery, electronics and semiconductor manufacturing.
Industrial motion control applications use specialized equipment and require system design and integration. Control systems play an important role in engineering. Fuzzy logic is the natural choice for designing control applications and is the most popular and appropriate for the control of home and industrial appliances.
Academic and industrial experts are constantly researching and proposing innovative and effective fuzzy control systems. This book is an edited volume Author: S. Ramakrishnan. Fuzzy Applications in Industrial Engineering (Studies in Fuzziness and Soft Computing) th Edition by Cengiz Kahraman (Editor) ISBN ISBN These major application areas are Control and Reliability, Engineering Economics and Investment Analysis, Group and Multi-criteria Decision-making, Human Factors Engineering and.The applications of soft sensors presented in this volume are designed to cope with the whole range from measuring system backup and what-if analysis through real-time prediction for plant control to sensor diagnosis and validation.
Some of the soft sensors developed here are implemented on-line at industrial plants. Features: • soft-sensor.An introductory book that provides theoretical, practical, and application coverage of the emerging field of type-2 fuzzy logic control.
Until recently, little was known about type-2 fuzzy controllers due to the lack of basic calculation methods available for type-2 fuzzy sets and logic—and many different aspects of type-2 fuzzy control still.