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Modeling for Nonlinear Systems by Use of RBF Network

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4 Author(s)
Liping Qu ; BeiHua Univ., Jilin ; Jianming Lu ; Yahagi, T. ; Yongyin Qu

This paper presents a means to make the model for nonlinear systems based on Radial Basis Function Neural Network (RBFNN).As a example, the high power DC graphitizing furnace is analyzed, and the RBF model of the system is constructed from experiments or simulations. The procedures for training the model are described along with discussions on error. All the simulated results show that the discussed approaches are effective.

Published in:

Control and Automation, 2007. ICCA 2007. IEEE International Conference on

Date of Conference:

May 30 2007-June 1 2007