Essentials of Fuzzy Modeling and Control

Essentials of Fuzzy Modeling and Control

Author: Ronald R. Yager

Publisher:

Published: 1994

Total Pages: 416

ISBN-13:

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This book offers a thorough introduction to the field of fuzzy logic with complete coverage of both relevant theory and applications. With its comprehensive presentation of fuzzy logic as well as coverage of both fuzzy control and modeling, this text is destined to become the classic primer in this quickly developing field.


Fuzzy Modeling and Control

Fuzzy Modeling and Control

Author: Andrzej Piegat

Publisher: Physica

Published: 2013-03-19

Total Pages: 737

ISBN-13: 3790818240

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In the last ten years, a true explosion of investigations into fuzzy modeling and its applications in control, diagnostics, decision making, optimization, pattern recognition, robotics, etc. has been observed. The attraction of fuzzy modeling results from its intelligibility and the high effectiveness of the models obtained. Owing to this the modeling can be applied for the solution of problems which could not be solved till now with any known conventional methods. The book provides the reader with an advanced introduction to the problems of fuzzy modeling and to one of its most important applications: fuzzy control. It is based on the latest and most significant knowledge of the subject and can be used not only by control specialists but also by specialists working in any field requiring plant modeling, process modeling, and systems modeling, e.g. economics, business, medicine, agriculture,and meteorology.


Fuzzy Modeling for Control

Fuzzy Modeling for Control

Author: Robert Babuška

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 269

ISBN-13: 9401148686

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Rule-based fuzzy modeling has been recognised as a powerful technique for the modeling of partly-known nonlinear systems. Fuzzy models can effectively integrate information from different sources, such as physical laws, empirical models, measurements and heuristics. Application areas of fuzzy models include prediction, decision support, system analysis, control design, etc. Fuzzy Modeling for Control addresses fuzzy modeling from the systems and control engineering points of view. It focuses on the selection of appropriate model structures, on the acquisition of dynamic fuzzy models from process measurements (fuzzy identification), and on the design of nonlinear controllers based on fuzzy models. To automatically generate fuzzy models from measurements, a comprehensive methodology is developed which employs fuzzy clustering techniques to partition the available data into subsets characterized by locally linear behaviour. The relationships between the presented identification method and linear regression are exploited, allowing for the combination of fuzzy logic techniques with standard system identification tools. Attention is paid to the trade-off between the accuracy and transparency of the obtained fuzzy models. Control design based on a fuzzy model of a nonlinear dynamic process is addressed, using the concepts of model-based predictive control and internal model control with an inverted fuzzy model. To this end, methods to exactly invert specific types of fuzzy models are presented. In the context of predictive control, branch-and-bound optimization is applied. The main features of the presented techniques are illustrated by means of simple examples. In addition, three real-world applications are described. Finally, software tools for building fuzzy models from measurements are available from the author.


Fuzzy Control

Fuzzy Control

Author: Shehu S. Farinwata

Publisher: John Wiley & Sons

Published: 2000-06-08

Total Pages: 424

ISBN-13:

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Fuzzy Control Synthesis and Analysis Edited by Shehu S. Farinwata Ford Motor Company, Research Laboratory, Dearborn, Michigan, USA Dimitar Filev Ford Motor Company, AMTDC, Redford, Michigan, USA Reza Langari Texas A & M University, College Station, Texas, USA Fuzzy techniques are used to cope with imprecision in the basic elements of a process under control. Written by an international team of researchers this edited volume covers the modeling, analysis and synthesis of fuzzy control systems. Features include: ? Comprehensive coverage of fuzzy dynamical systems, robustness, stability and sensitivity -- giving the reader a good grasp of the fundamentals of fuzzy control ? Focus on the analytical structures of new fuzzy modeling approaches based on the Takagi-Sugeno-Kang (TSK) or Takagi-Sugeno (TS) model ? Applications of fuzzy control to aircraft systems, rocket engines and automotive engines ? Problems and examples illustrating how fuzzy approaches may be applied to the modeling, analysis and synthesis of closed-loop systems Design and control engineers will value the advanced control techniques and new design and analysis tools presented. Postgraduates studying fuzzy control will find this book a useful reference on synthesis, systems analysis and advanced nonlinear control methods.


Fuzzy Logic, Identification and Predictive Control

Fuzzy Logic, Identification and Predictive Control

Author: Jairo Jose Espinosa Oviedo

Publisher: Springer Science & Business Media

Published: 2007-01-04

Total Pages: 274

ISBN-13: 1846280877

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Modern industrial processes and systems require adaptable advanced control protocols able to deal with circumstances demanding "judgement” rather than simple "yes/no”, "on/off” responses: circumstances where a linguistic description is often more relevant than a cut-and-dried numerical one. The ability of fuzzy systems to handle numeric and linguistic information within a single framework renders them efficacious for this purpose. Fuzzy Logic, Identification and Predictive Control first shows you how to construct static and dynamic fuzzy models using the numerical data from a variety of real industrial systems and simulations. The second part exploits such models to design control systems employing techniques like data mining. This monograph presents a combination of fuzzy control theory and industrial serviceability that will make a telling contribution to your research whether in the academic or industrial sphere and also serves as a fine roundup of the fuzzy control area for the graduate student.


Introduction To Type-2 Fuzzy Logic Control

Introduction To Type-2 Fuzzy Logic Control

Author: Jerry Mendel

Publisher: John Wiley & Sons

Published: 2014-06-16

Total Pages: 470

ISBN-13: 1118901444

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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 needed to be investigated in order to advance this new and powerful technology. This self-contained reference covers everything readers need to know about the growing field. Written with an educational focus in mind, Introduction to Type-2 Fuzzy Logic Control: Theory and Applications uses a coherent structure and uniform mathematical notations to link chapters that are closely related, reflecting the book’s central themes: analysis and design of type-2 fuzzy control systems. The book includes worked examples, experiment and simulation results, and comprehensive reference materials. The book also offers downloadable computer programs from an associated website. Presented by world-class leaders in type-2 fuzzy logic control, Introduction to Type-2 Fuzzy Logic Control: Is useful for any technical person interested in learning type-2 fuzzy control theory and its applications Offers experiment and simulation results via downloadable computer programs Features type-2 fuzzy logic background chapters to make the book self-contained Provides an extensive literature survey on both fuzzy logic and related type-2 fuzzy control Introduction to Type-2 Fuzzy Logic Control is an easy-to-read reference book suitable for engineers, researchers, and graduate students who want to gain deep insight into type-2 fuzzy logic control.


Fuzzy Systems Engineering

Fuzzy Systems Engineering

Author: Witold Pedrycz

Publisher: John Wiley & Sons

Published: 2007-10-12

Total Pages: 550

ISBN-13: 0470168951

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A self-contained treatment of fuzzy systems engineering, offering conceptual fundamentals, design methodologies, development guidelines, and carefully selected illustrative material Forty years have passed since the birth of fuzzy sets, in which time a wealth of theoretical developments, conceptual pursuits, algorithmic environments, and other applications have emerged. Now, this reader-friendly book presents an up-to-date approach to fuzzy systems engineering, covering concepts, design methodologies, and algorithms coupled with interpretation, analysis, and underlying engineering knowledge. The result is a holistic view of fuzzy sets as a fundamental component of computational intelligence and human-centric systems. Throughout the book, the authors emphasize the direct applicability and limitations of the concepts being discussed, and historical and bibliographical notes are included in each chapter to help readers view the developments of fuzzy sets from a broader perspective. A radical departure from current books on the subject, Fuzzy Systems Engineering presents fuzzy sets as an enabling technology whose impact, contributions, and methodology stretch far beyond any specific discipline, making it applicable to researchers and practitioners in engineering, computer science, business, medicine, bioinformatics, and computational biology. Additionally, three appendices and classroom-ready electronic resources make it an ideal textbook for advanced undergraduate- and graduate-level courses in engineering and science.


Fuzzy Systems and Knowledge Discovery

Fuzzy Systems and Knowledge Discovery

Author: Lipo Wang

Publisher: Springer Science & Business Media

Published: 2005-08-17

Total Pages: 1354

ISBN-13: 3540283315

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This book and its sister volume, LNAI 3613 and 3614, constitute the proce- ings of the Second International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2005), jointly held with the First International Conference on Natural Computation (ICNC 2005, LNCS 3610, 3611, and 3612) from - gust 27–29, 2005 in Changsha, Hunan, China. FSKD 2005 successfully attracted 1249 submissions from 32 countries/regions (the joint ICNC-FSKD 2005 received 3136 submissions). After rigorous reviews, 333 high-quality papers, i. e. , 206 long papers and 127 short papers, were included in the FSKD 2005 proceedings, r- resenting an acceptance rate of 26. 7%. The ICNC-FSKD 2005 conference featured the most up-to-date research - sults in computational algorithms inspired from nature, including biological, e- logical, and physical systems. It is an exciting and emerging interdisciplinary area in which a wide range of techniques and methods are being studied for dealing with large, complex, and dynamic problems. The joint conferences also promoted cross-fertilization over these exciting and yet closely-related areas, which had a signi?cant impact on the advancement of these important technologies. Speci?c areas included computation with words, fuzzy computation, granular com- tation, neural computation, quantum computation, evolutionary computation, DNA computation, chemical computation, information processing in cells and tissues, molecular computation, arti?cial life, swarm intelligence, ants colony, arti?cial immune systems, etc. , with innovative applications to knowledge d- covery, ?nance, operations research, and more.


Fuzzy Control and Fuzzy Systems

Fuzzy Control and Fuzzy Systems

Author: Witold Pedrycz

Publisher: *Research Studies Press

Published: 1993-08-17

Total Pages: 376

ISBN-13:

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Examines the methodology and algorithms of fuzzy sets considered mainly in the context of control engineering and system modelling and analysis. Special emphasis is focused on the processing of fuzzy information realized with the aid of fuzzy relational structures and their extensions.


Fuzzy Models in Economics

Fuzzy Models in Economics

Author: Gorkhmaz Imanov

Publisher: Springer Nature

Published: 2020-10-07

Total Pages: 113

ISBN-13: 3030612821

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This book offers a timely guide to fuzzy methods applied to the analysis of socioeconomic systems. It provides readers with a comprehensive and up-to-date overview of the algorithms, including the theory behind them, as well as practical considerations, current limitations and solutions. Each chapter focuses on a different economic problem, explaining step by step the process to approach it, using the corresponding fuzzy tools. The book covers elements of intuitionistic fuzzy logics, fuzzy entropy and the fuzzy DEMATEL method, a fuzzy approach to calculate the financial stability index. It also reports on some new models of social, financial and ecological security, and on a novel fuzzy method for evaluating the quality of development of information economy.