DocumentCode :
325193
Title :
Noise rejection in parameters identification for piecewise linear fuzzy models
Author :
Simani, S. ; Fantuzzi, C. ; Rovatti, R. ; Beghelli, S.
Author_Institution :
Eng. Dept., Ferrara Univ., Italy
Volume :
1
fYear :
1998
fDate :
4-9 May 1998
Firstpage :
378
Abstract :
The fuzzy model identification problem from noisy data is addressed. The piecewise linear fuzzy model structure is used as a nonlinear prototype for a multi-input, single-output unknown system. The consequent of the fuzzy model is identified using noisy data, e.g. collected from experiments on a real system. The identification procedure is formulated within the Frisch scheme, well established for linear systems, which has been modified and improved to be applied in fuzzy systems field
Keywords :
fuzzy systems; multivariable systems; noise; parameter estimation; uncertain systems; Frisch scheme; multi-input single-output unknown system; noise rejection; noisy data; parameters identification; piecewise linear fuzzy models; Ear; Fuzzy systems; Least squares methods; Linear systems; Linearity; Noise reduction; Parameter estimation; Piecewise linear approximation; Piecewise linear techniques; Systems engineering and theory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems Proceedings, 1998. IEEE World Congress on Computational Intelligence., The 1998 IEEE International Conference on
Conference_Location :
Anchorage, AK
ISSN :
1098-7584
Print_ISBN :
0-7803-4863-X
Type :
conf
DOI :
10.1109/FUZZY.1998.687515
Filename :
687515
Link To Document :
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