Fuzzy Decision Making In Modeling And Control


Fuzzy Decision Making In Modeling And Control
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Fuzzy Decision Making In Modeling And Control


Fuzzy Decision Making In Modeling And Control
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Author : Joao M. C. Sousa
language : en
Publisher: World Scientific
Release Date : 2002

Fuzzy Decision Making In Modeling And Control written by Joao M. C. Sousa and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Computers categories.


Decision making and control are two fields with distinct methods for solving problems, and yet they are closely related. This book bridges the gap between decision making and control in the field of fuzzy decisions and fuzzy control, and discusses various ways in which fuzzy decision making methods can be applied to systems modeling and control.Fuzzy decision making is a powerful paradigm for dealing with human expert knowledge when one is designing fuzzy model-based controllers. The combination of fuzzy decision making and fuzzy control in this book can lead to novel control schemes that improve the existing controllers in various ways. The following applications of fuzzy decision making methods for designing control systems are considered: OCo Fuzzy decision making for enhancing fuzzy modeling. The values of important parameters in fuzzy modeling algorithms are selected by using fuzzy decision making.OCo Fuzzy decision making for designing signal-based fuzzy controllers. The controller mappings and the defuzzification steps can be obtained by decision making methods.OCo Fuzzy design and performance specifications in model-based control. Fuzzy constraints and fuzzy goals are used.OCo Design of model-based controllers combined with fuzzy decision modules. Human operator experience is incorporated for the performance specification in model-based control.The advantages of bringing together fuzzy control and fuzzy decision making are shown with multiple examples from real and simulated control systems."



Fuzzy Decision Making In Modeling And Control


Fuzzy Decision Making In Modeling And Control
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language : en
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Fuzzy Modeling For Control


Fuzzy Modeling For Control
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Author : Robert Babuška
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Fuzzy Modeling For Control written by Robert Babuška and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Mathematics categories.


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 Logic Control


Fuzzy Logic Control
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Author : H. B. Verbruggen
language : en
Publisher: World Scientific
Release Date : 1999

Fuzzy Logic Control written by H. B. Verbruggen and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Technology & Engineering categories.


Fuzzy logic control has become an important methodology in control engineering. This volume deals with applications of fuzzy logic control in various domains. The contributions are divided into three parts. The first part consists of two state-of-the-art tutorials on fuzzy control and fuzzy modeling. Surveys of advanced methodologies are included in the second part. These surveys address fuzzy decision making and control, fault detection, isolation and diagnosis, complexity reduction in fuzzy systems and neuro-fuzzy methods. The third part contains application-oriented contributions from various fields, such as process industry, cement and ceramics, vehicle control and traffic management, electromechanical and production systems, avionics, biotechnology and medical applications. The book is intended for researchers both from the academic world and from industry.



Fuzzy Algorithms For Control


Fuzzy Algorithms For Control
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Author : H. B. Verbruggen
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-09

Fuzzy Algorithms For Control written by H. B. Verbruggen and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-09 with Mathematics categories.


Fuzzy Algorithms for Control gives an overview of the research results of a number of European research groups that are active and play a leading role in the field of fuzzy modeling and control. It contains 12 chapters divided into three parts. Chapters in the first part address the position of fuzzy systems in control engineering and in the AI community. State-of-the-art surveys on fuzzy modeling and control are presented along with a critical assessment of the role of these methodologists in control engineering. The second part is concerned with several analysis and design issues in fuzzy control systems. The analytical issues addressed include the algebraic representation of fuzzy models of different types, their approximation properties, and stability analysis of fuzzy control systems. Several design aspects are addressed, including performance specification for control systems in a fuzzy decision-making framework and complexity reduction in multivariable fuzzy systems. In the third part of the book, a number of applications of fuzzy control are presented. It is shown that fuzzy control in combination with other techniques such as fuzzy data analysis is an effective approach to the control of modern processes which present many challenges for the design of control systems. One has to cope with problems such as process nonlinearity, time-varying characteristics for incomplete process knowledge. Examples of real-world industrial applications presented in this book are a blast furnace, a lime kiln and a solar plant. Other examples of challenging problems in which fuzzy logic plays an important role and which are included in this book are mobile robotics and aircraft control. The aim of this book is to address both theoretical and practical subjects in a balanced way. It will therefore be useful for readers from the academic world and also from industry who want to apply fuzzy control in practice.



Fuzzy Systems


Fuzzy Systems
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Author : Hung T. Nguyen
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Fuzzy Systems written by Hung T. Nguyen and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Mathematics categories.


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.



Insight Into Fuzzy Modeling


Insight Into Fuzzy Modeling
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Author : Vilém Novák
language : en
Publisher: John Wiley & Sons
Release Date : 2016-04-04

Insight Into Fuzzy Modeling written by Vilém Novák and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-04 with Technology & Engineering categories.


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.



Fuzzy Modeling And Control


Fuzzy Modeling And Control
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Author : Andrzej Piegat
language : en
Publisher: Physica
Release Date : 2013-03-19

Fuzzy Modeling And Control written by Andrzej Piegat and has been published by Physica this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-19 with Computers categories.


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 Multicriteria Decision Making


Fuzzy Multicriteria Decision Making
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Author : Witold Pedrycz
language : en
Publisher: John Wiley & Sons
Release Date : 2011-06-15

Fuzzy Multicriteria Decision Making written by Witold Pedrycz and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-06-15 with Technology & Engineering categories.


Fuzzy Multicriteria Decision-Making: Models, Algorithms and Applications addresses theoretical and practical gaps in considering uncertainty and multicriteria factors encountered in the design, planning, and control of complex systems. Including all prerequisite knowledge and augmenting some parts with a step-by-step explanation of more advanced concepts, the authors provide a systematic and comprehensive presentation of the concepts, design methodology, and detailed algorithms. These are supported by many numeric illustrations and a number of application scenarios to motivate the reader and make some abstract concepts more tangible. Fuzzy Multicriteria Decision-Making: Models, Algorithms and Applications will appeal to a wide audience of researchers and practitioners in disciplines where decision-making is paramount, including various branches of engineering, operations research, economics and management; it will also be of interest to graduate students and senior undergraduate students in courses such as decision making, management, risk management, operations research, numerical methods, and knowledge-based systems.



Multistage Fuzzy Control


Multistage Fuzzy Control
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Author : Janusz Kacprzyk
language : en
Publisher: Wiley-Blackwell
Release Date : 2012-08-02

Multistage Fuzzy Control written by Janusz Kacprzyk and has been published by Wiley-Blackwell this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-08-02 with Fuzzy systems categories.


This valuable and timely publication from a highly acclaimed expert in the field provides an overall view of the discipline of multistage fuzzy control as well as a wealth of new ideas in decision-making and reinforcement learning Multistage Fuzzy Control 2nd Edition follows its predecessor, a classic in the field, in explaining the essential principles of fuzzy logic and describing both the theoretical and practical advantages of a model-based, prescriptive approach. In the 10 years since the first edition however, a myriad of new perspectives and developments have emerged - many as a result of the author s own research that earned him the 2006 IEEE Computational Intelligence Society Fuzzy Systems Pioneer Award for pioneering works on multistage fuzzy control. The use of some fuzzy tools for the analysis and optimization of multistage decision-making and control, notably of a fuzzy dynamic programming type, is now considered important and popular with researchers from different fields. This new edition features 30% new material in both theory and applications, with much space devoted to new research into reinforcement learning (a sub-area of machine learning concerned with how actions are to be taken in an environment so as to maximize some long term reward), and also to some extensions towards fuzzy reinforcement learning or neurofuzzy reinforcement learning. It also includes many new elements related to IT (information technology), notably to data mining, learning, bioinformatics, etc. Multistage Fuzzy Control 2nd Edition is an essential handbook for those wishing to resolve real-world problems in control and decision analysis through the use of fuzzy-logic-based methods. Offers a valuable and timely publication from a highly acclaimed expert in the field, providing an overall view of the discipline of multistage fuzzy control as well as a wealth of new research. Presents 30% new material, including important new ideas such as reinforcement learning, neurofuzzy architectures, evolutionary optimization and applications in the areas of bioinformatics, mobile robots and computer communication. Includes a range of new applications related to power engineering, such as the use of fuzzy dynamic programming for water reservoir control, mobile robot control, data transfer control in computer networks, sequential pattern mining and predicting the secondary structure of ribonucleic acid (and some other problems in bioinformatics.