Adaptive Control with Recurrent High-order Neural Networks: Theory and Industrial Applications

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CN101493677B - 一种神经网络的系统控制器结构及系统辨识结构 - Google Patents

Learn how to enable JavaScript on your browser. See All Customer Reviews. Shop Books. Add to Wishlist. USD Sign in to Purchase Instantly. Overview 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 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.


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  • CNB - 一种神经网络的系统控制器结构及系统辨识结构 - Google Patents;

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. Different readers will find different aspects of the development of interest.

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The last chapter of the monograph discusses the problem of manufacturing or production process scheduling. Product Details Table of Contents. Table of Contents 1. Indirect Adaptive Control.

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