On-line linear system parameter estimation using the neo-fuzzy-neuron algorithm

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 effecti...

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Bibliographic Details
Published in2003 2nd IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications pp. 115 - 118
Main Authors Bacelar, A.S., de Souza Filho, E.B., Neves, F.A.S., Landim, R.P.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2003
Subjects
Control systems
Convergence
Electronic mail
Filters
Fuzzy logic
Fuzzy sets
Linear systems
Neural networks
Parameter estimation
Temperature dependence
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ISBN0780381386
9780780381384
DOI10.1109/IDAACS.2003.1249529

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Summary: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
ISBN:0780381386
9780780381384
DOI:10.1109/IDAACS.2003.1249529