Identification of the Hydraulic AGC System of Cold Rolling Mill using RBF Neural Network

Huiyong Chen Huiyong Chen,Shanghong He Shanghong He

doi:10.1109/wcica.2006.1712574

Identification of the Hydraulic AGC System of Cold Rolling Mill using RBF Neural Network

Huiyong Chen Huiyong Chen, Shanghong He Shanghong He

https://doi.org/10.1109/wcica.2006.1712574

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Publication Date: Jan 1, 2006

Citations: 3

Affiliation: Changsha University of Science and Technology

#Radial Basis Function Network #Radial Basis Function Network Structure + Show 8 more

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Abstract

The characteristics of hydraulic automatic gage control System(AGC) of cold rolling mill is analyzed. the principle of identification using Radial Basis Function(RBF) network is introduced. The RBF network structure, train algorithm are given in detail. Finally, the nonlinear model of HAGC is established with RBF network. To improving the accuracy of identification. the input and output data is filtered with wavelet denoising technique. The experimental results indicate that the combination of wavelet denoising and RBF network can provide an efficient method for system identification.

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