A novel approach to robust parameter estimation using neurofuzzy systems

da Silva, I. N.; de Arruda, LVR; do Amaral, W. C.

Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/8911

Title:

A novel approach to robust parameter estimation using neurofuzzy systems

Author(s):

Institution:

Universidade Estadual Paulista (UNESP)
Fed Ctr Educ Technol
Universidade Estadual de Campinas (UNICAMP)

ISSN:

0378-4754

Abstract:

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. (C) 1999 IMACS/Elsevier B.V. B.V. All rights reserved.

Issue Date:

1-Feb-1999

Citation:

Mathematics and Computers In Simulation. Amsterdam: Elsevier B.V., v. 48, n. 3, p. 251-268, 1999.

Time Duration:

251-268

Publisher:

Elsevier B.V.

Keywords:

robust parameter estimation
neurofuzzy system
artificial intelligence
neural networks

Source:

http://dx.doi.org/10.1016/S0378-4754(98)00161-X

URI:

Access Rights:

Acesso restrito

Type:

outro

Source:

http://repositorio.unesp.br/handle/11449/8911

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