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“A Genetic Approach to the Identification of Linear Dynamical Systems with Static Nonlinearities”

Al-Duwaish, H. (2000) “A Genetic Approach to the Identification of Linear Dynamical Systems with Static Nonlinearities”. International Journal of Systems Science, 31 (3). pp. 307-314.

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Abstract

This paper investigates the use of genetic algorithms in the identification of linear systems with static nonlinearitites. Linear systems with static nonlinearities at the input known as the Hammerstein model, and linear systems with static nonlinearities at the output known as the Wiener model are considered in this paper. The parameters of the Hammerstein and the Wiener models are estimated using genetic algorithms from the input-output data by minimizing the error between the true model output and the identified model output. Using genetic algorithms, the Hammerstein and the Wiener models with known nonlinearity structure and unknown parameters can be identified. Moreover, systems with non-minimum phase characteristics can be identified. Extensive simulations have been used to study the convergence properties of the proposed scheme. Simulation examples are included to demonstrate the effectiveness and robustness of the proposed identification scheme



Item Type:Article
Date:2000
Subjects:Electrical
Divisions:College Of Engineering Sciences > Electrical Engineering Dept
Creators:Al-Duwaish, H.
Email:Al-Duwaish hduwaish@kfupm.edu.sa
ID Code:695
Deposited By:AYHAM ZAZA
Deposited On:24 Mar 2008 16:36
Last Modified:12 Apr 2011 13:06

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