Abstract
This paper presents a neural network based controller used in commanding time varying systems with uncertainties task First, a reduction procedure of the initial set of parameters using an unsupervised pattern recognition technique was applied. After this a feed-forward neural network was trained using the minimized set of data. The advantage of this method is over-passing of the difficulties implied by the direct solving of the differential models, which are necessary in a classical approach. An application of a missile-target tracking was implemented using the mentioned method, and the results are compared with those obtain in a classical approach.
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© 1999 Springer-Verlag Berlin Heidelberg
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Grigore, O., Grigore, O. (1999). The Control of a Nonlinear System Using Neural Networks. In: Reusch, B. (eds) Computational Intelligence. Fuzzy Days 1999. Lecture Notes in Computer Science, vol 1625. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48774-3_72
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DOI: https://doi.org/10.1007/3-540-48774-3_72
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-66050-7
Online ISBN: 978-3-540-48774-6
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