DocumentCode
2347644
Title
On-line linear system parameter estimation using the neo-fuzzy-neuron algorithm
Author
Bacelar, A.S. ; de Souza Filho, E.B. ; Neves, F.A.S. ; Landim, R.P.
Author_Institution
Univ. Fed. de Pernambuco, Recife
fYear
2003
fDate
8-10 Sept. 2003
Firstpage
115
Lastpage
118
Abstract
A method for estimating the parameters of a single input single output (SISO) model is proposed and discussed. The new method is based on the neo-fuzzy-neuron algorithm and has the property of fast convergence, which makes it suitable for online estimation. In order to evaluate the estimator effectiveness, it was applied to obtain the parameters of a second-order filter. Simulation and experimental results are presented
Keywords
discrete time filters; fuzzy neural nets; linear systems; parameter estimation; convergence; neo-fuzzy-neuron algorithm; neural networks; online linear system parameter estimation; second-order filter; single input single output model; Control systems; Convergence; Electronic mail; Filters; Fuzzy logic; Fuzzy sets; Linear systems; Neural networks; Parameter estimation; Temperature dependence;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, 2003. Proceedings of the Second IEEE International Workshop on
Conference_Location
Lviv
Print_ISBN
0-7803-8138-6
Type
conf
DOI
10.1109/IDAACS.2003.1249529
Filename
1249529
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