DocumentCode :
1666045
Title :
A model prediction for non-rational models via Radial Basis Function network
Author :
Fernando, Gómez Salas ; Wang, Yongji
Author_Institution :
Dept. of Control Sci. & Eng., Huazhong Univ. of Sci. & Technol., Wuhan, China
fYear :
2010
Firstpage :
813
Lastpage :
818
Abstract :
Rational models have been gradually adopted in various applications of nonlinear systems in the area of the systems identification and control because they have the advantage of modeling certain types of discontinuous functions and even severe non-linearilities using only a very few parameters. Based on the principle of Radial Basis Function even with noisy regressors, this work presents an alternative approach for the model prediciton of non-linear rational models. Two examples are included to show the performance of the proposed methodology.
Keywords :
identification; nonlinear systems; prediction theory; radial basis function networks; rational functions; regression analysis; discontinuous functions; model prediction; nonlinear rational model; nonrational model; radial basis function network; systems identification; Instruction sets;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Modelling, Identification and Control (ICMIC), The 2010 International Conference on
Conference_Location :
Okayama
Print_ISBN :
978-1-4244-8381-5
Electronic_ISBN :
978-0-9555293-3-7
Type :
conf
Filename :
5553612
Link To Document :
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