A hybrid modeling method based on mechanism analysis, identification and RBF neural networks

Author

Yang, Xuhua ; Dai, Huaping ; Sun, Youxian

Author_Institution

Inst. of Modern Control Eng., Zhejiang Univ., Hangzhou, China

Volume

2

fYear

2003

fDate

5-8 Oct. 2003

Firstpage

1310

Abstract

This paper proposed a hybrid modeling method based on mechanism analysis, identification and RBF neural networks. First, Get a industrial object´s low-order model by the mechanism analysis and identification method. Second, adopt RBF neural networks modeling method to compensate unmodeled high-order model. The sum of the low-order model and high-order model is the hybrid model. This kind of hybrid model has more accuracy than a model which is gotten by mechanism analysis and identification method and has more generalization capability than a model which is gotten by neural networks modeling method.

Keywords

generalisation (artificial intelligence); identification; radial basis function networks; RBF neural networks; generalization; hybrid modeling; identification; mechanism analysis; radial basis function neural networks; unmodeled high-order model; Control engineering; Industrial control; Laboratories; Manufacturing industries; Manufacturing processes; Mathematical model; Modems; Neural networks; Predictive models; Sun;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man and Cybernetics, 2003. IEEE International Conference on

ISSN

1062-922X

Print_ISBN

0-7803-7952-7

Type

conf

DOI

10.1109/ICSMC.2003.1244592

Filename

1244592