Access this book
Tax calculation will be finalised at checkout
Other ways to access
Table of contents (14 chapters)
-
Front Matter
-
Back Matter
Keywords
About this book
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.
Editors and Affiliations
Bibliographic Information
Book Title: Fuzzy Systems
Book Subtitle: Modeling and Control
Editors: Hung T. Nguyen, Michio Sugeno
Series Title: The Handbooks of Fuzzy Sets
DOI: https://doi.org/10.1007/978-1-4615-5505-6
Publisher: Springer New York, NY
-
eBook Packages: Springer Book Archive
Copyright Information: Springer Science+Business Media New York 1998
Hardcover ISBN: 978-0-7923-8064-1Published: 31 July 1998
Softcover ISBN: 978-1-4613-7515-9Published: 12 October 2012
eBook ISBN: 978-1-4615-5505-6Published: 06 December 2012
Series ISSN: 1388-4352
Edition Number: 1
Number of Pages: XXI, 519
Topics: Mathematical Logic and Foundations, Discrete Mathematics, Electrical Engineering, Operations Research/Decision Theory, Mechanical Engineering, Artificial Intelligence