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Abstract: In this paper we present a short introduction to the theory of neural control. Universal approximation, on- and off-line learning ability and parallelism of neural networks are the main motivation for their application to modelling and control problems. This has led to several existing neural control strategies. An overview of methods is presented, with emphasis on the foundations of neural optimal control, stability theory and nonlinear system identification using neural networks for... (Update)
Context of citations to this paper: More
...such as Neurofuzzy systems [37] or mixed with PI and PD controllers. Overviews of other nonlinear systems are given in [8] 15] 18] and [28]. All of these models are based on the same principle: how to provide a mathematical relationship between a given input and a given...
.... [20] 26] 58] or mixed with PI and PD controllers [31] 61] 63] Overviews of nonlinear systems are given in [16] 22] 28] 42] [45] and [48] All of these models are based on the same principle: how to provide a mathematical relationship between a given input and a...
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BibTeX entry: (Update)
Suykens J. A. K., Bersini H., "Neural Control Theory: an Overview", Journal A, Vol. 37, No. 3, 1996, pp. 4 - 10. http://citeseer.ist.psu.edu/suykens96neural.html More
@misc{ bersini96neural,
author = "S. Bersini",
title = "Neural Control Theory: an Overview",
text = "Suykens J. A. K., Bersini H., Neural Control Theory: an Overview, Journal
A, Vol. 37, No. 3, 1996, pp. 4 - 10.",
year = "1996",
url = "citeseer.ist.psu.edu/suykens96neural.html" }
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