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Adaptive Control with Recurrent High-order Neural Networks - Theory and Industrial Applications (Paperback, Softcover reprint of the original 1st ed. 2000)
Loot Price: R2,764
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Adaptive Control with Recurrent High-order Neural Networks - Theory and Industrial Applications (Paperback, Softcover reprint of the original 1st ed. 2000)
Series: Advances in Industrial Control
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The series Advances in Industrial Control aims to report and
encourage technology transfer in control engineering. The rapid
development of control technology has an impact on all areas of the
control discipline. New theory, new controllers, actuators,
sensors, new industrial processes, computer methods, new
applications, new philosophies ... , new challenges. Much of this
development work resides in industrial reports, feasibility study
papers and the reports of advanced collaborative projects. The
series offers an opportunity for researchers to present an extended
exposition of such new work in all aspects of industrial control
for wider and rapid dissemination. Neural networks is one of those
areas where an initial burst of enthusiasm and optimism leads to an
explosion of papers in the journals and many presentations at
conferences but it is only in the last decade that significant
theoretical work on stability, convergence and robustness for the
use of neural networks in control systems has been tackled. George
Rovithakis and Manolis Christodoulou have been interested in these
theoretical problems and in the practical aspects of neural network
applications to industrial problems. This very welcome addition to
the Advances in Industrial Control series provides a succinct
report of their research. The neural network model at the core of
their work is the Recurrent High Order Neural Network (RHONN) and a
complete theoretical and simulation development is presented.
Different readers will find different aspects of the development of
interest. The last chapter of the monograph discusses the problem
of manufacturing or production process scheduling.
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