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Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Automatic control engineering
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Stable Adaptive Neural Network Control (Hardcover, 2002 ed.)
Loot Price: R5,302
Discovery Miles 53 020
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Stable Adaptive Neural Network Control (Hardcover, 2002 ed.)
Series: The International Series on Asian Studies in Computer and Information Science, 13
Expected to ship within 18 - 22 working days
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Recent years have seen a rapid development of neural network
control tech niques and their successful applications. Numerous
simulation studies and actual industrial implementations show that
artificial neural network is a good candidate for function
approximation and control system design in solving the control
problems of complex nonlinear systems in the presence of different
kinds of uncertainties. Many control approaches/methods, reporting
inventions and control applications within the fields of adaptive
control, neural control and fuzzy systems, have been published in
various books, journals and conference proceedings. In spite of
these remarkable advances in neural control field, due to the
complexity of nonlinear systems, the present research on adaptive
neural control is still focused on the development of fundamental
methodologies. From a theoretical viewpoint, there is, in general,
lack of a firmly mathematical basis in stability, robustness, and
performance analysis of neural network adaptive control systems.
This book is motivated by the need for systematic design approaches
for stable adaptive control using approximation-based techniques.
The main objec tives of the book are to develop stable adaptive
neural control strategies, and to perform transient performance
analysis of the resulted neural control systems analytically. Other
linear-in-the-parameter function approximators can replace the
linear-in-the-parameter neural networks in the controllers
presented in the book without any difficulty, which include
polynomials, splines, fuzzy systems, wavelet networks, among
others. Stability is one of the most important issues being
concerned if an adaptive neural network controller is to be used in
practical applications."
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