Stable Adaptive Control and Estimation for Nonlinear Systems
Neural and Fuzzy Approximator Techniques
Published on 12. June 2002
Book
Hardback
XX, 548 pages
978-0-471-41546-6 (ISBN)
Description
Includes a solution manual for problems.
* Provides MATLAB code for examples and solutions.
* Deals with robust systems in both theory and practice.
Reviews / Votes
"...well-organized...very useful for a graduate level control or intelligent systems course..." (International Journal of Robust and Nonlinear Control, January 2005) "...the text is well organised with topics judiciously selected to build on each other...the discussion and motivations are rigorous..." (International Journal of Robust & Nonlinear Control, Vol.15, No.1, 10th January 2005)"...this is an excellent book. It is pedagogically sound and, hence, suitable as a text for graduate courses.... I recommend it also as a very valuable resource to practitioners..." (International Journal of General Systems, Vol. 32, 2003)
More details
Product info
gebunden
Series
Edition
1. Auflage
Language
English
Place of publication
United States
Publishing group
John Wiley & Sons Inc
Target group
College/higher education
Professional and scholarly
Product notice
sewn/stitched
Cloth over boards
Dimensions
Height: 240 mm
Width: 161 mm
Thickness: 35 mm
Weight
1012 gr
ISBN-13
978-0-471-41546-6 (9780471415466)
Schweitzer Classification
Other editions
Additional editions
Jeffrey T. Spooner | Manfredi Maggiore | Raúl Ordóñez
Stable Adaptive Control and Estimation for Nonlinear Systems
Neural and Fuzzy Approximator Techniques
E-Book
03/2004
Wiley
€159.99
Available for download
Persons
JEFFREY T. SPOONER is a senior member of the technical staff at Sandia National Laboratories, Albuquerque, New Mexico.
MANFREDI MAGGIORE is an assistant professor in the Department of Electrical and Computer Engineering at the University of Toronto, Canada.
RAÚL ORDÓÑEZ is an assistant professor in the Department of Electrical and Computer Engineering at the University of Dayton, Ohio.
KEVIN M. PASSINO is a professor in the Department of Electrical Engineering at The Ohio State University.
Content
Introduction.
PART I: FOUNDATIONS.
Mathematical Foundations.
Neural Networks and Fuzzy Systems.
Optimization for Training Approximators.
Function Approximation.
PART II: STATE-FEEDBACK CONTROL.
Control of Nonlinear Systems.
Direct Adaptive Control.
Indirect Adaptive Control.
Implementations and Comparative Studies.
PART III:OUTPUT-FEEDBACK CONTROL.
Output-Feedback Control.
Adaptive Output Feedback Control.
Applications.
PART IV: EXTENSIONS.
Discrete-Time Systems.
Decentralized Systems.
Perspectives on Intelligent Adaptive Systems.
For Further Study.
Bibliography.
Index.