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Fuzzy Modeling and Fuzzy Control, Zhang Huaguang, Liu Derong



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Цена: 13974р.
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Автор: Zhang Huaguang, Liu Derong
Название:  Fuzzy Modeling and Fuzzy Control
Перевод названия: Нечеткое моделирование и нечеткий контроль
ISBN: 9780817644918
Издательство: Springer
Классификация:
ISBN-10: 0817644911
Обложка/Формат: Hardback
Страницы: 416
Вес: 0.791 кг.
Дата издания: 2006
Серия: Control Engineering
Язык: English
Издание: 2006 ed.
Иллюстрации: 161 black & white illustrations, 50 black & white
Размер: 23.37 x 16.21 x 2.49
Читательская аудитория: Professional & vocational
Ссылка на Издательство: Link
Рейтинг:
Поставляется из: Германии
Описание: Fuzzy logic methodology is effective in dealing with complex nonlinear systems containing uncertainties that are tough to model. Technology based on this methodology has been applied to real-world problems, especially in consumer products. This book presents treatment of fuzzy modeling and fuzzy control, offering tools for control of such systems.
Дополнительное описание: Формат: 235x155
Илюстрации: 161
Круг читателей: Graduate students and researchers in electrical, computer, chemical, civil, mechanical, aeronautical, manufacturing, and industrial engineering, computer science, and physical sciences, applied mathematicians, control engineers, computer scientists, and p
Ключевые слова: fuzzy logic
fuzzy modeling
fuzzy control
nonlinear systems with uncertainties
Mamdani fuzzy model
Takagi–Sugeno fuzzy model
fuzzy hyperbolic model
fuzzy inference
stability, robustness, optimality
fuzzy performance evaluators
fuzzy sliding mode control
Язык: eng
Оглавление: PrefaceFuzzy Set Theory and Rough Set TheoryIdentification of the Takagi–Sugeno Fuzzy ModelFuzzy Model Identification Based on Rough Set Data AnalysisIdentification of the Fuzzy Hyperbolic ModelBasic Methods for Fuzzy Inference and ControlFuzzy Inference and Control Methods Involving Two Kinds of UncertaintiesFuzzy Control Schemes via a Fuzzy Performance EvaluatorMultivariable Predictive Control Based on the T–S Fuzzy ModelAdaptive Control Methods Based on Fuzzy Basis Function VectorsController Design Based on the Fuzzy Hyperbolic ModelFuzzy H-infinity Filter Design for Nonlinear Discrete-Time Systems with Multiple Time-DelaysChaotification of the Fuzzy Hyperbolic ModelFeedforward Fuzzy Control Approach Using the Fourier IntegralIndex 





Analytical Methods in Fuzzy Modeling and Control

Автор: Jacek Kluska
Название: Analytical Methods in Fuzzy Modeling and Control
ISBN: 3642100643 ISBN-13(EAN): 9783642100642
Издательство: Springer
Рейтинг:
Цена: 19589 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.

Fuzzy Control and Identification

Автор: Lilly
Название: Fuzzy Control and Identification
ISBN: 0470542772 ISBN-13(EAN): 9780470542774
Издательство: Wiley
Рейтинг:
Цена: 16782 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.

Control of Electric Machine Drive Systems

Автор: Sul
Название: Control of Electric Machine Drive Systems
ISBN: 0470590793 ISBN-13(EAN): 9780470590799
Издательство: Wiley
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Цена: 20901 р.
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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.

Modeling Uncertainty with Fuzzy Logic

Автор: Asli Celikyilmaz; I. Burhan T?rksen
Название: Modeling Uncertainty with Fuzzy Logic
ISBN: 3642100635 ISBN-13(EAN): 9783642100635
Издательство: Springer
Рейтинг:
Цена: 27251 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book presents an uncertainty modeling approach using a new type of fuzzy system model via "Fuzzy Functions". It also reviews standard tools of fuzzy system modeling approaches to demonstrate the novelty of the structurally different fuzzy function.

Fuzzy Neural Networks for Real Time Control Applications

Автор: Erdal Kayacan
Название: Fuzzy Neural Networks for Real Time Control Applications
ISBN: 0128026871 ISBN-13(EAN): 9780128026878
Издательство: Elsevier Science
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Цена: 11549 р.
Наличие на складе: Нет в наличии.

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 doctorate university studies. We hope that this book will serve its main purpose successfully.


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