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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Xiu, Z.H., Zhang, J.S., Zheng, Y.L.: Bionics in Computational Intelligence. Science Press, Beijing (2003)
Honik, K., Stinchcombe, M., Whiter, H.: Mutilayer Feedforward Networks are Universal Approximators. Neural Networks 2, 359–366 (1989)
Honik, K.: Approximation capabilities of multilayer feedforwad networks neural. Neural Network 4, 551–557 (1991)
Yuan, X.M., Li, H.Y., Liu, S.K., et al.: The Application of Neural Network and Genetic Algorithm in the Area of Water Science. China Water Power Press, Beijing (2002)
Yin, J.C., Wang, L.D., Wang, N.N.: A Variable-Structure Gradient RBF Network with its Application to Predictive Ship Motion Control. Asian Journal of Control, doi:10.1002/asjc.343 (in press)
Zhang, Q., Benveniste, A.: Wavelet Networks. IEEE Transctions on Neural Networks 3, 889–898 (1992)
Chen, J.N.: Basis of Wavelet Analysis. Shanghai University Press, Shanghai (2002)
Guo, Y.J., Zhang, S.C.: Wavelet Neural Network Estimation Model for Mine Safety. Journal of Northeastern University (Natural Science) 27, 702–705 (2006)
Zhang, H.Y., Lin, H.: Option Pricing Models Based on Wavelet Neural Network. Journal of Southeast University (Natural Science Edition) 37, 716–720 (2007)
Hsieh, S.P., Hwang, T.S.: Dynamic Modeling and Neural Network Self-Tuning PID Control Design for a Linear Motor Driving Platform. IEEE Transactions on Electrical and Electronic Engineering 5, 701–707 (2010)
Gao, S.X., Cao, S.F., Zhang, Y.: Research On PID Control Based on BP Neural Network and Its Application. In: Proc. 2010 2nd International Asia Conference on Informatics in Control, Automation and Robotics, pp. 91–94 (2010)
Jia, X.L., Yang, Y.S.: Mathematic Model of Ship Motion. Dalian Maritime University Press, Dalian (1998)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
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
Download citation
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
eBook Packages: Computer ScienceComputer Science (R0)