Parameter Estimation Of Wiener-Hammerstein Models Via Genetic Algorithms

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
Depositing User: SYED AMEENUDDIN HUSSAIN
Date Deposited: 14 Jun 2008 13:39
Last Modified: 01 Nov 2019 16:44
URI: http://eprints.kfupm.edu.sa/id/eprint/2542