A novel approach to robust parameter estimation using neurofuzzy systems
A novel approach for solving robust parameter estimation problems is presented for processes with unknown-but-bounded errors and uncertainties. An artificial neural network is developed to calculate a membership set for model parameters. Techniques of fuzzy logic control lead the network to its equilibrium points. Simulated examples are presented as an illustration of the proposed technique. The result represent a significant improvement over previously proposed methods.
Year of publication: |
1999
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Authors: | Silva, Ivan N. da ; Arruda, Lucia V.R. de ; Amaral, Wagner C. do |
Published in: |
Mathematics and Computers in Simulation (MATCOM). - Elsevier, ISSN 0378-4754. - Vol. 48.1999, 3, p. 251-268
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Publisher: |
Elsevier |
Subject: | Robust parameter estimation | Neurofuzzy system | Artificial intelligence | Neural networks |
Saved in:
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