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Author : Fernando Matia,G. Nicolás Marichal,Emilio Jimenez
Publisher : Unknown
Page : 306 pages
File Size : 41,7 Mb
Release : 2014-09-30
Category : Electronic
ISBN : 9462390835
Author : Terrell Harvey,Dallas Mullins
Publisher : Unknown
Page : 74 pages
File Size : 40,9 Mb
Release : 2018-06-05
Category : Electronic
ISBN : 1536134147
Fuzzy Modeling and Control: Methods, Applications and Research opens by recommending a new fuzzy RANSAC algorithm based on the reinforcement learning concept to improve modeling performance under the outlier noise. The authors also propose a novel methodology for online modeling of multivariable Hammerstein evolving fuzzy models with minimum realization in state space from experimental data. Results characterized by strongly coupled nonlinearities demonstrate the computational efficiency of the proposed methodology. Later, two types of neural networks are applied to find the approximate solutions of the fully fuzzy nonlinear system, and a superior gradient descent algorithm is proposed in order to train the neural networks. Lastly, the authors propose a novel online evolving fuzzy Takagi-Sugeno state-space model identification approach for nonlinear multivariable systems. To circumvent "the curse of dimensionality", the algorithm uses tools for monitoring the quality of the existing clusters. (Novinka)
Author : Robert Babuška
Publisher : Springer Science & Business Media
Page : 269 pages
File Size : 46,6 Mb
Release : 2012-12-06
Category : Mathematics
ISBN : 9789401148689
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.
Author : Andrzej Piegat
Publisher : Physica
Page : 737 pages
File Size : 53,5 Mb
Release : 2013-03-19
Category : Computers
ISBN : 9783790818246
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.
Author : Fernando Matía,G. Nicolás Marichal,Emilio Jiménez
Publisher : Springer
Page : 288 pages
File Size : 41,6 Mb
Release : 2014-08-14
Category : Technology & Engineering
ISBN : 9789462390829
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 they express the personal point of view of the author. This book compiles the developments of researchers with demonstrated experience in the field of fuzzy control following a logic structure and a unified the style. The first chapters of the book are dedicated to the introduction of the main fuzzy logic techniques, where the following chapters focus on concrete applications. This book is supported by the EUSFLAT and CEA-IFAC societies, which include a large number of researchers in the field of fuzzy logic and control. The central topic of the book, Fuzzy Control, is one of the main research and development lines covered by these associations.
Author : Hung T. Nguyen,Michio Sugeno
Publisher : Springer Science & Business Media
Page : 532 pages
File Size : 47,7 Mb
Release : 2012-12-06
Category : Mathematics
ISBN : 9781461555056
The analysis and control of complex systems have been the main motivation for the emergence of fuzzy set theory since its inception. It is also a major research field where many applications, especially industrial ones, have made fuzzy logic famous. This unique handbook is devoted to an extensive, organized, and up-to-date presentation of fuzzy systems engineering methods. The book includes detailed material and extensive bibliographies, written by leading experts in the field, on topics such as: Use of fuzzy logic in various control systems. Fuzzy rule-based modeling and its universal approximation properties. Learning and tuning techniques for fuzzy models, using neural networks and genetic algorithms. Fuzzy control methods, including issues such as stability analysis and design techniques, as well as the relationship with traditional linear control. Fuzzy sets relation to the study of chaotic systems, and the fuzzy extension of set-valued approaches to systems modeling through the use of differential inclusions. Fuzzy Systems: Modeling and Control is part of The Handbooks of Fuzzy Sets Series. The series provides a complete picture of contemporary fuzzy set theory and its applications. This volume is a key reference for systems engineers and scientists seeking a guide to the vast amount of literature in fuzzy logic modeling and control.
Author : Jacek Kluska
Publisher : Springer Science & Business Media
Page : 272 pages
File Size : 43,9 Mb
Release : 2009-03-10
Category : Computers
ISBN : 9783540899266
This book is focused on mathematical analysis and rigorous design methods for fuzzy control systems based on Takagi-Sugeno fuzzy models, sometimes called Takagi-Sugeno-Kang models. The author presents a rather general analytical theory of exact fuzzy modeling and control of continuous and discrete-time dynamical systems. Main attention is paid to usability of the results for the control and computer engineering community and therefore simple and easy knowledge-bases for linguistic interpretation have been used. The approach is based on the author’s theorems concerning equivalence between widely used Takagi-Sugeno systems and some class of multivariate polynomials. It combines the advantages of fuzzy system theory and classical control theory. Classical control theory can be applied to modeling of dynamical plants and the controllers. They are all equivalent to the set of Takagi-Sugeno type fuzzy rules. The approach combines the best of fuzzy and conventional control theory. It enables linguistic interpretability (also called transparency) of both the plant model and the controller. In the case of linear systems and some class of nonlinear systems, engineers can in many cases directly apply well-known classical tools from the control theory both for analysis, and the design of closed-loop fuzzy control systems. Therefore the main objective of the book is to establish comprehensive and unified analytical foundations for fuzzy modeling using the Takagi-Sugeno rule scheme and their applications for fuzzy control, identification of some class of nonlinear dynamical processes and classification problem solver design.
Author : Gang Feng
Publisher : CRC Press
Page : 299 pages
File Size : 47,6 Mb
Release : 2018-09-03
Category : Technology & Engineering
ISBN : 9781420092653
Fuzzy logic control (FLC) has proven to be a popular control methodology for many complex systems in industry, and is often used with great success as an alternative to conventional control techniques. However, because it is fundamentally model free, conventional FLC suffers from a lack of tools for systematic stability analysis and controller design. To address this problem, many model-based fuzzy control approaches have been developed, with the fuzzy dynamic model or the Takagi and Sugeno (T–S) fuzzy model-based approaches receiving the greatest attention. Analysis and Synthesis of Fuzzy Control Systems: A Model-Based Approach offers a unique reference devoted to the systematic analysis and synthesis of model-based fuzzy control systems. After giving a brief review of the varieties of FLC, including the T–S fuzzy model-based control, it fully explains the fundamental concepts of fuzzy sets, fuzzy logic, and fuzzy systems. This enables the book to be self-contained and provides a basis for later chapters, which cover: T–S fuzzy modeling and identification via nonlinear models or data Stability analysis of T–S fuzzy systems Stabilization controller synthesis as well as robust H∞ and observer and output feedback controller synthesis Robust controller synthesis of uncertain T–S fuzzy systems Time-delay T–S fuzzy systems Fuzzy model predictive control Robust fuzzy filtering Adaptive control of T–S fuzzy systems A reference for scientists and engineers in systems and control, the book also serves the needs of graduate students exploring fuzzy logic control. It readily demonstrates that conventional control technology and fuzzy logic control can be elegantly combined and further developed so that disadvantages of conventional FLC can be avoided and the horizon of conventional control technology greatly extended. Many chapters feature application simulation examples and practical numerical examples based on MATLAB®.
Author : Michael Margaliot,Gideon Langholz
Publisher : World Scientific
Page : 204 pages
File Size : 53,9 Mb
Release : 2000
Category : Technology & Engineering
ISBN : 9810243340
Fuzzy logic has found applications in an incredibly wide range of areas in the relatively wide range of areas in the relatively short time since its conception. It was invented by Lotfi Zadeh, a leading systems expert, so it is perhaps not surprising that system theory is one of the areas in which fuzzy logic has made a profound impact. Fuzzy logic combined with the paradigm of computing with words allows the use and manipulation of human knowledge and reasoning in the modeling and control of dynamical systems. This monograph presents new approaches to the construction of fuzzy models and to the design of fuzzy controllers. The emphasis is on developing methods that allow systematic design on the one hand and mathematical analysis of the resulting system on the other. In particular, the methods described allow rigorous analysis of the stability and robustness of the systems, which are crucial issues in control theory. The first theme of the book is a new approach to the system design and analysis of fuzzy controllers, given linguistic information concerning the plant and the control objective. The new approach, fuzzy Lyapunov synthesis, is a computing-with-words version of the well-known (classical) Lyapunov synthesis method. The second theme of the book is to show that fuzzy controllers are in fact solutions to a nonlinear optimal control problem. The authors formulate a novel nonlinear optimal control problem, consisting of a new state-space model -- referred to as the hyperbolic state-space model -- and a new cost functional and show that its solution is a fuzzy controller. This leads to a new framework for fuzzy modeling and control that combines the advantages of the fuzzyworld, such as linguistic interpretability, and of classical optimal control theory, such as guaranteed stability and robustness.
Author : Hung T. Nguyen,Nadipuram R. Prasad
Publisher : CRC Press
Page : 446 pages
File Size : 40,5 Mb
Release : 1999-03-30
Category : Computers
ISBN : 0849328845
This collection compiles the seminal contributions of Michio Sugeno on fuzzy systems and technologies. Fuzzy Modeling & Control: Selected Works of Sugeno serves as a singular resource that provides a clear, comprehensive treatment of fuzzy control systems. The book comprises two parts fuzzy system identification and modeling systems control Each part outlines the fundamentals of fuzzy logic and covers essential material for understanding the mathematical and modeling details in Sugeno's works. Introductory chapters include extended summaries of each paper or group of papers, suggesting where the theories discussed might be useful in application.
Author : Ronald R. Yager,Dimitar P. Filev
Publisher : Unknown
Page : 416 pages
File Size : 40,6 Mb
Release : 1994
Category : Computers
ISBN : UOM:39015032210422
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.
Author : Zhong Li
Publisher : Springer
Page : 300 pages
File Size : 50,8 Mb
Release : 2006-08-02
Category : Computers
ISBN : 9783540332213
This book presents the fundamental concepts of fuzzy logic and fuzzy control, chaos theory and chaos control. It also provides a definition of chaos on the metric space of fuzzy sets. The book raises many questions and generates a great potential to attract more attention to combine fuzzy systems with chaos theory. In this way it contains important seeds for future scientific research and engineering applications.
Author : Jerry Mendel,Hani Hagras,Woei-Wan Tan,William W. Melek,Hao Ying
Publisher : John Wiley & Sons
Page : 376 pages
File Size : 47,8 Mb
Release : 2014-06-16
Category : Technology & Engineering
ISBN : 9781118901441
An introductory book that provides theoretical, practical,and application coverage of the emerging field of type-2 fuzzylogic control Until recently, little was known about type-2 fuzzy controllersdue to the lack of basic calculation methods available for type-2fuzzy sets and logic—and many different aspects of type-2fuzzy control still needed to be investigated in order to advancethis new and powerful technology. This self-contained referencecovers everything readers need to know about the growing field. Written with an educational focus in mind, Introduction toType-2 Fuzzy Logic Control: Theory and Applications uses acoherent structure and uniform mathematical notations to linkchapters that are closely related, reflecting the book’scentral themes: analysis and design of type-2 fuzzy controlsystems. The book includes worked examples, experiment andsimulation results, and comprehensive reference materials. The bookalso offers downloadable computer programs from an associatedwebsite. 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 learningtype-2 fuzzy control theory and its applications Offers experiment and simulation results via downloadablecomputer programs Features type-2 fuzzy logic background chapters to make thebook self-contained Provides an extensive literature survey on both fuzzy logic andrelated type-2 fuzzy control Introduction to Type-2 Fuzzy Logic Control is aneasy-to-read reference book suitable for engineers, researchers,and graduate students who want to gain deep insight into type-2fuzzy logic control.
Author : Vilém Novák,Irina Perfilieva,Antonín Dvorák
Publisher : John Wiley & Sons
Page : 268 pages
File Size : 43,5 Mb
Release : 2016-04-04
Category : Technology & Engineering
ISBN : 9781119193180
Provides a unique and methodologically consistent treatment of various areas of fuzzy modeling and includes the results of mathematical fuzzy logic and linguistics This book is the result of almost thirty years of research on fuzzy modeling. It provides a unique view of both the theory and various types of applications. The book is divided into two parts. The first part contains an extensive presentation of the theory of fuzzy modeling. The second part presents selected applications in three important areas: control and decision-making, image processing, and time series analysis and forecasting. The authors address the consistent and appropriate treatment of the notions of fuzzy sets and fuzzy logic and their applications. They provide two complementary views of the methodology, which is based on fuzzy IF-THEN rules. The first, more traditional method involves fuzzy approximation and the theory of fuzzy relations. The second method is based on a combination of formal fuzzy logic and linguistics. A very important topic covered for the first time in book form is the fuzzy transform (F-transform). Applications of this theory are described in separate chapters and include image processing and time series analysis and forecasting. All of the mentioned components make this book of interest to students and researchers of fuzzy modeling as well as to practitioners in industry. Features: Provides a foundation of fuzzy modeling and proposes a thorough description of fuzzy modeling methodology Emphasizes fuzzy modeling based on results in linguistics and formal logic Includes chapters on natural language and approximate reasoning, fuzzy control and fuzzy decision-making, and image processing using the F-transform Discusses fuzzy IF-THEN rules for approximating functions, fuzzy cluster analysis, and time series forecasting Insight into Fuzzy Modeling is a reference for researchers in the fields of soft computing and fuzzy logic as well as undergraduate, master and Ph.D. students. Vilém Novák, D.Sc. is Full Professor and Director of the Institute for Research and Applications of Fuzzy Modeling, University of Ostrava, Czech Republic. Irina Perfilieva, Ph.D. is Full Professor, Senior Scientist, and Head of the Department of Theoretical Research at the Institute for Research and Applications of Fuzzy Modeling, University of Ostrava, Czech Republic. Antonín Dvorák, Ph.D. is Associate Professor, and Senior Scientist at the Institute for Research and Applications of Fuzzy Modeling, University of Ostrava, Czech Republic.
Author : Hao Ying
Publisher : Wiley-IEEE Press
Page : 350 pages
File Size : 49,5 Mb
Release : 2000-08-15
Category : Computers
ISBN : STANFORD:36105028497670
The emerging, powerful fuzzy control paradigm has led to the worldwide success of countless commercial products and real-world applications. Fuzzy control is exceptionally practical and cost-effective due to its unique ability to accomplish tasks without knowing the mathematical model of the system, even if it is nonlinear, time varying and complex. Nevertheless, compared with the conventional control technology, most fuzzy control applications are developed in an ad hoc manner with little analytical understanding and without rigorous system analysis and design. Fuzzy Control and Modeling is the only book that establishes the analytical foundations for fuzzy control and modeling in relation to the conventional linear and nonlinear theories of control and systems. The coverage is up-to-date, comprehensive, in-depth and rigorous. Numeric examples and applications illustrate the utility of the theoretical development. Important topics discussed include: Structures of fuzzy controllers/models with respect to conventional fuzzy controllers/models Analysis of fuzzy control and modeling in relation to their classical counterparts Stability analysis of fuzzy systems and design of fuzzy control systems Sufficient and necessary conditions on fuzzy systems as universal approximators Real-time fuzzy control systems for treatment of life-critical problems in biomedicine Fuzzy Control and Modeling is a self-contained, invaluable resource for professionals and students in diverse technical fields who aspire to analytically study fuzzy control and modeling.