Parameter estimation of nonlinear system based on hybrid intelligent method

Parameter estimation of nonlinear system using hybrid intelligent method is presented. A recursive least squares estimation combined with genetic algorithm is used in this study. A recurrent neural network for system identification and a conventional parameter estimation using recursive least-square...

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Bibliographic Details
Main Authors: JUANG, Jih-Gau, LIN, Bo-Shian, LI, Chien-Kuo
Format: Conference Proceeding
Language:English
Subjects:
Applied sciences
Computer science
control theory
systems
Control theory. Systems
Exact sciences and technology
Genetics
Modelling and identification
Neural networks
Neurofeedback
Neurons
Nonlinear systems
Parameter estimation
Recurrent neural networks
Recursive estimation
Resonance light scattering
System identification
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Description
Summary:Parameter estimation of nonlinear system using hybrid intelligent method is presented. A recursive least squares estimation combined with genetic algorithm is used in this study. A recurrent neural network for system identification and a conventional parameter estimation using recursive least-squares method are also given for comparison. After test, the proposed scheme has better performance on parameter estimation than the conventional least-squares estimation and the recurrent neural network.
ISSN:1062-922X
2577-1655
DOI:10.1109/ICSMC.2004.1400862