Parameter Estimation Of Wiener-Hammerstein Models Via Genetic Algorithms
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 mod...
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| Other Authors: | , , |
| Format: | article |
| Published: |
2020
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| Subjects: | |
| Online Access: | https://eprints.kfupm.edu.sa/id/eprint/2542/1/16.pdf |
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| Summary: | 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 |
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