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Parameter Estimation Of Wiener-Hammerstein Models Via Genetic Algorithms

Emara-Shabaik, Husam and Abdel-Magid, YL and Al-Ajmi, KH Parameter Estimation Of Wiener-Hammerstein Models Via Genetic Algorithms. ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING, 25. pp. 49-61.

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Abstract

Conventional methods of estimating model parameters have difficulties with both nonlinear systems and with systems operating in noisy environments. In this paper, a modified genetic algorithm is used as a procedure to solve the parameter identification problem of the nonlinear Wiener-Hammerstein models. Numerical simulations are presented to illustrate the effectiveness of the proposed algorithm based on different input signals, and different noise-to-signal ratios of the output. Also, the algorithm is applied to model a DC generator with some nonlinear characteristics



Item Type:Article
Subjects:Systems
Divisions:College Of Computer Sciences and Engineering > Systems Engineering Dept
Creators:Emara-Shabaik, Husam and Abdel-Magid, YL and Al-Ajmi, KH
Email:shabaik@kfupm.edu.sa, UNSPECIFIED, UNSPECIFIED
ID Code:2542
Deposited By:SYED AMEENUDDIN HUSSAIN
Deposited On:14 Jun 2008 13:39
Last Modified:12 Apr 2011 13:13

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