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 |
| Department: | College of Computing and Mathematics > lndustrial and Systems Engineering |
| Depositing User: | SYED AMEENUDDIN HUSSAIN |
| Date Deposited: | 14 Jun 2008 10:39 |
| Last Modified: | 01 Nov 2019 13:44 |
| URI: | http://eprints.kfupm.edu.sa/id/eprint/2542 |