Fuzzy Modeling and Fuzzy Control, Zhang Huaguang, Liu Derong
Автор: Lilly Название: Fuzzy Control and Identification ISBN: 0470542772 ISBN-13(EAN): 9780470542774 Издательство: Wiley Рейтинг: Цена: 11146 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A fuzzy control system is a control system based on fuzzy logic, which is a mathematical system that analyzes analog input values in terms of logical variables that take on continuous values between 0 and 1. This text provides a broad introduction to fuzzy control and identification, covering both Mamdani and Takagi-Sugeno fuzzy systems.
Автор: Ma Zongmin Название: Fuzzy Database Modeling with XML ISBN: 0387242481 ISBN-13(EAN): 9780387242484 Издательство: Springer Рейтинг: Цена: 14629 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Fuzzy Database Modeling with XML aims to provide a single record of current research and practical applications in the fuzzy databases. This volume is the outgrowth of research the author has conducted in recent years. Fuzzy Database Modeling with XML introduces state-of-the-art information to the database research, while at the same time serving the information technology professional faced with a non-traditional application that defeats conventional approaches.The research on fuzzy conceptual models and fuzzy object-oriented databases is receiving increasing attention, in addition to fuzzy relational database models. With rapid advances in network and internet techniques as well, the databases have been applied under the environment of distributed information systems. It is essential in this case to integrate multiple fuzzy database systems. Since databases are commonly employed to store and manipulate XML data, additional requirements are necessary to model fuzzy information with XML. Secondly, this book maps fuzzy XML model to the fuzzy databases. Very few efforts at investigating these issues have thus far occurred.Fuzzy Database Modeling with XML is designed for a professional audience of researchers and practitioners in industry. This book is also suitable for graduate-level students in computer science.
Описание: This book provides the latest developments in the analysis and control of nonlinear time-delay systems using T-S fuzzy model approach. It presents, in a single volume, a fairly comprehensive, up-to-date and detailed treatment of many interesting topics such as stability analysis, stabilization, fuzzy variable structure control, fuzzy tracking control,fuzzy observer design and filter design for T-S fuzzy systems with time delay. Insights to solve relevant problems are highlighted. Advanced analysis and synthesis methods used in the text incluse augmented Lyapunov functionals, free-weighting matrix techniques, relaxed linear metrix inequalities and matrix decoupling methods. The book is a useful source of reference for all those, from graduate students to senior researchers in a wide range of areas from mathematics and engineering to human and social sciences, interested in orworking with fuzzy systems.
Автор: Erdal Kayacan Название: Fuzzy Neural Networks for Real Time Control Applications ISBN: 0128026871 ISBN-13(EAN): 9780128026878 Издательство: Elsevier Science Рейтинг: Цена: 7414 р. Наличие на складе: Поставка под заказ.
Описание: AN INDISPENSABLE RESOURCE FOR ALL THOSE WHO DESIGN AND IMPLEMENT TYPE-1 AND TYPE-2 FUZZY NEURAL NETWORKS IN REAL TIME SYSTEMS. . Delve into the type-2 fuzzy logic systems and become engrossed in the parameter update algorithms for type-1 and type-2 fuzzy neural networks and their stability analysis with this book!. . Not only does this book stand apart from others in its focus but also in its application-based presentation style. Prepared in a way that can be easily understood by those who are experienced and inexperienced in this field. Readers can benefit from the computer source codes for both identification and control purposes which are given at the end of the book. . A clear and an in-depth examination has been made of all the necessary mathematical foundations, type-1 and type-2 fuzzy neural network structures and their learning algorithms as well as their stability analysis. . . You will find that each chapter is devoted to a different learning algorithm for the tuning of type-1 and type-2 fuzzy neural networks; some of which are:. • Gradient descent. • Levenberg-Marquardt. • Extended Kalman filter. . In addition to the aforementioned conventional learning methods above, number of novel sliding mode control theory-based learning algorithms, which are simpler and have closed forms, and their stability analysis have been proposed. Furthermore, hybrid methods consisting of particle swarm optimization and sliding mode control theory-based algorithms have also been introduced. The potential readers of this book are expected to be the undergraduate and graduate students, engineers, mathematicians and computer scientists. Not only can this book be used as a reference source for a scientist who is interested in fuzzy neural networks and their real-time implementations but also as a course book of fuzzy neural networks or artificial intelligence in master or d
Автор: Piegat Andrzej Название: Fuzzy Modeling and Control ISBN: 3790813850 ISBN-13(EAN): 9783790813852 Издательство: Springer Рейтинг: Цена: 24976 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 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.
Автор: Babuska Название: Fuzzy Modeling for Control ISBN: 0792381548 ISBN-13(EAN): 9780792381549 Издательство: Springer Рейтинг: Цена: 26021 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Rule-based fuzzy modeling has been recognised as a powerful technique for the modeling of partly-known nonlinear systems. Fuzzy models can integrate information from different sources, such as physical laws, empirical models, measurements and heuristics. This title addresses fuzzy modeling from the systems and control engineering points of view.
Автор: Jacek Kluska Название: Analytical Methods in Fuzzy Modeling and Control ISBN: 3642100643 ISBN-13(EAN): 9783642100642 Издательство: Springer Рейтинг: Цена: 14648 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 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.
Автор: Sul Название: Control of Electric Machine Drive Systems ISBN: 0470590793 ISBN-13(EAN): 9780470590799 Издательство: Wiley Рейтинг: Цена: 14438 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Based on the author`s industry experience and collaborative works with other industries, Control of Electric Machine Drive System is packed with implemented, tested, and verified ideas that relate to everyday problems in the field.
Автор: Bertoluzza Carlo, Gil Maria A., Ralescu Dan A. Название: Statistical Modeling, Analysis and Management of Fuzzy Data ISBN: 3790814407 ISBN-13(EAN): 9783790814408 Издательство: Springer Рейтинг: Цена: 17241 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The contributions in this book connect Probability Theory/Statistics and Fuzzy Set Theory in different ways. Some of these connections are either philosophical or theoretical in nature, but most of them state models and methods to work with fuzzy data (or fuzzy perception) when dealing with random experiments. In this way, several probabilistic studies are developed, as well as techniques and criteria to get descriptive and inferential statistical conclusions from fuzzy data. On the other hand, some studies have been devoted to fuzzy measures and their relationship with measures in Probability Theory.
Описание: This monograph presents the latest advances of fuzzy logic and soft computing in reservoir characterization and modeling. It proposes for the first time that future develoments require perception-based information processing. The book presents important steps in this direction by introducing fuzzy partial differential equations and relational equations. It provides a unique opportunity for soft computing researchers and oil industry practitioners to understand the significance of the changes in the fields by presenting recent accomplishments and new directions.
Описание: This book presents recent advances for imprecise and uncertain engineering information from the point of view of fuzzy database modeling. The topics include fuzzy conceptual data modeling of engineering information, conversion of the fuzzy conceptual models, and database implementation of the fuzzy conceptual data models. Some major data and database models for engineering information modeling are investigated. The main novel aspect of this book is that the book focuses on imprecise and uncertain industrial information modeling viewed from databases and fuzzy database technologies viewed from industrial applications. This may be useful for people involved in theory research, design implementation, and application development of intelligent engineering databases.
Название: Fuzzy Logic and Hydrological Modeling ISBN: 1439809399 ISBN-13(EAN): 9781439809396 Издательство: Taylor&Francis Рейтинг: Цена: 19058 р. Наличие на складе: Поставка под заказ.
Описание: The hydrological sciences typically present with grey or fuzzy information making them an appropriate challenge for fuzzy logic application. This book includes
chapters that elucidate the fuzzy logic principles, processes, and design for an inference system with many hydrological examples.
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