Stable Adaptive Control and Estimation for Nonlinear Systems: Neural and Fuzzy Approximator Techniques...

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Jeffrey T. Spooner (Sandia National Laboratories) Manfredi Maggiore (University of Toronto)

Stable Adaptive Control and Estimation for Nonlinear Systems

Neural and Fuzzy Approximator Techniques

Jeffrey T. Spooner (Sandia National Laboratories), Manfredi Maggiore (University of Toronto), Raúl Ordóñez (University of Dayton) , Kevin M. Passino (The Ohio State University)

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English

Wiley-Interscience
10 May 2002

Non-linear science; Automatic control engineering

Series: Adaptive and Cognitive Dynamic Systems: Signal Processing, Learning, Communications and Control

Includes a solution manual for problems. Provides MATLAB code for examples and solutions. Deals with robust systems in both theory and practice.

By: Jeffrey T. Spooner (Sandia National Laboratories), Manfredi Maggiore (University of Toronto), Raúl Ordóñez (University of Dayton), Kevin M. Passino (The Ohio State University)
Imprint: Wiley-Interscience
Country of Publication: United States
Dimensions: Height: 244mm, Width: 159mm, Spine: 31mm
Weight: 912g
ISBN: 9780471415466
ISBN 10: 0471415464
Series: Adaptive and Cognitive Dynamic Systems: Signal Processing, Learning, Communications and Control
Pages: 568
Publication Date: 10 May 2002
Audience: College/higher education , Professional and scholarly , Professional & Vocational , A / AS level , Further / Higher Education
Format: Hardback
Publisher's Status: Active

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.

Reviews for Stable Adaptive Control and Estimation for Nonlinear Systems: Neural and Fuzzy Approximator Techniques

...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)