Fuzzy Modeling and Fuzzy Control, Zhang Huaguang, Liu Derong
Автор: Piegat Andrzej Название: Fuzzy Modeling and Control ISBN: 3790813850 ISBN-13(EAN): 9783790813852 Издательство: Springer Рейтинг: Цена: 35492 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: 36977 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: Lilly Название: Fuzzy Control and Identification ISBN: 0470542772 ISBN-13(EAN): 9780470542774 Издательство: Wiley Рейтинг: Цена: 17515 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: Sul Название: Control of Electric Machine Drive Systems ISBN: 0470590793 ISBN-13(EAN): 9780470590799 Издательство: Wiley Рейтинг: Цена: 22688 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.
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.
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.
Описание: Foundations of Fuzzy Control: A Practical Approach, 2nd Edition has been significantly revised and updated, with two new chapters on Gain Scheduling Control and Neurofuzzy Modelling.
Автор: Shehu S. Farinwata Название: Fuzzy Control: Synthesis and Analysis ISBN: 0471986313 ISBN-13(EAN): 9780471986317 Издательство: Wiley Рейтинг: Цена: 25864 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This text examines synthetic and dynamical properties of fuzzy control systems in a quantitative manner. It includes fuzzy dynamical systems, controllability and sensitivity analysis and how these affect parameters in membership functions, fuzzification, defuzzification and inferencing.
Описание: Focuses on mathematical analysis and rigorous design methods for fuzzy control systems based on Takagi-Sugeno fuzzy models, sometimes called Takagi-Sugeno-Kang models. This title presents a rather general analytical theory of exact fuzzy modeling and control of continuous and discrete-time dynamical systems.
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.
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