A highly accessible and unified approach to the design and analysis
of intelligent control systems
Adaptive Approximation Based Control is a tool every control
designer should have in his or her control toolbox.
Mixing approximation theory, parameter estimation, and feedback
control, this book presents a unified approach designed to enable
readers to apply adaptive approximation based control to existing
systems, and, more importantly, to gain enough intuition and
understanding to manipulate and combine it with other control tools
for applications that have not been encountered before.
The authors provide readers with a thought-provoking framework for
rigorously 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 approximator
parameters be guaranteed?
* Can control systems be designed to be robust in the face of
noise, disturbances, and unmodeled effects?
* Can this approach handle significant changes in the dynamics due
to such disruptions as system failure?
* What types of nonlinear dynamic systems are amenable to this
approach?
* What are the limitations of adaptive approximation based
control?
Combining theoretical formulation and design techniques with
extensive use of simulation examples, this book is a stimulating
text for researchers and graduate students and a valuable resource
for practicing engineers.
Circa l’autore
JAY A. FARRELL, Ph D, is Professor and former chair of the
Department of Electrical Engineering at the University of
California at Riverside. He was also principal investigator on
projects involving intelligent and learning control systems for
autonomous vehiclesat the Charles Stark Draper Laboratory, where he
was awarded the Engineering Vice President’s Best Technical
Publication Award. He is the author of one other book and over 130
articles for technical publications.
MARIOS M. POLYCARPOU, Ph D, is Professor and Interim Head
of the Department of Electrical and Computer Engineering at the
University of Cyprus. Dr. Polycarpou is the Editor in Chief of the
IEEE Transactions on Neural Networks. He is an IEEE Fellow and has
published more than 150 articles for journals, books, and
conference proceedings. Dr. Polycarpou was also the recipient of
the William H. Middendorf Research Excellence Award at the
University of Cincinnati.
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