Abstract
A time-delay wavelet neural network (TDWNN) is introduced to realize system identification based on model of nonlinear auto-regressive with exogenous inputs (NARX). The method incorporates the delayed massage and the gradient message of the system, is able to reflect the changing tendency of system. Multi-objective optimization method is used to estimate the network coefficient. The wavelet-network-based identification model is used for online system identification, and the experiment result of ship course control proved the efficiency of the identification model.
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© 2012 Springer-Verlag Berlin Heidelberg
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Zhang, W., Liu, Z., Xue, M. (2012). Time-Delay Wavelet Neural Networks Model with Application to Ship Control. In: Wang, J., Yen, G.G., Polycarpou, M.M. (eds) Advances in Neural Networks – ISNN 2012. ISNN 2012. Lecture Notes in Computer Science, vol 7368. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31362-2_47
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DOI: https://doi.org/10.1007/978-3-642-31362-2_47
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31361-5
Online ISBN: 978-3-642-31362-2
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