Abstract
Two different approaches that can provide frequent and accurate estimates of process outputs which are subject to large measurement delays are outlined. The first is based upon linear adaptive techniques whilst the other makes use of a fixed parameter neural network model. The results of applications to industrial data are used to discuss and contrast the performance capabilities of the two techniques.
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© 1991 Springer-Verlag
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Tham, M.T., Montague, G.A., Julian Morris, A. (1991). Process estimation: Linear adaptive algorithms and neural networks. In: Warwick, K., Kárný, M., Halousková, A. (eds) Advanced Methods in Adaptive Control for Industrial Applications. Lecture Notes in Control and Information Sciences, vol 158. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0003820
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DOI: https://doi.org/10.1007/BFb0003820
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