Farrell / Polycarpou Adaptive Approximation Based Control

Unifying Neural, Fuzzy and Traditional Adaptive Approximation Approaches
1. Auflage 2006
ISBN: 978-0-471-78180-6
Verlag: John Wiley & Sons
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 440 Seiten, E-Book

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

A highly accessible and unified approach to the design and analysisof intelligent control systems
Adaptive Approximation Based Control is a tool every controldesigner should have in his or her control toolbox.
Mixing approximation theory, parameter estimation, and feedbackcontrol, this book presents a unified approach designed to enablereaders to apply adaptive approximation based control to existingsystems, and, more importantly, to gain enough intuition andunderstanding to manipulate and combine it with other control toolsfor applications that have not been encountered before.
The authors provide readers with a thought-provoking framework forrigorously considering such questions as:
* What properties should the function approximator have?
* Are certain families of approximators superior to others?
* Can the stability and the convergence of the approximatorparameters be guaranteed?
* Can control systems be designed to be robust in the face ofnoise, disturbances, and unmodeled effects?
* Can this approach handle significant changes in the dynamics dueto such disruptions as system failure?
* What types of nonlinear dynamic systems are amenable to thisapproach?
* What are the limitations of adaptive approximation basedcontrol?
Combining theoretical formulation and design techniques withextensive use of simulation examples, this book is a stimulatingtext for researchers and graduate students and a valuable resourcefor practicing engineers.

Autoren/Hrsg.

Farrell, Jay A.

Polycarpou, Marios M.

Über Autor(innen)

JAY A. FARRELL, PhD, is Professor and former chair of theDepartment of Electrical Engineering at the University ofCalifornia at Riverside. He was also principal investigator onprojects involving intelligent and learning control systems forautonomous vehiclesat the Charles Stark Draper Laboratory, where hewas awarded the Engineering Vice President's Best TechnicalPublication Award. He is the author of one other book and over 130articles for technical publications.
MARIOS M. POLYCARPOU, PhD, is Professor and Interim Headof the Department of Electrical and Computer Engineering at theUniversity of Cyprus. Dr. Polycarpou is the Editor in Chief of theIEEE Transactions on Neural Networks. He is an IEEE Fellow and haspublished more than 150 articles for journals, books, andconference proceedings. Dr. Polycarpou was also the recipient ofthe William H. Middendorf Research Excellence Award at theUniversity of Cincinnati.