Fast identification of Wiener-Hammerstein systems using discrete optimisation

M. Schoukens; G. Vandersteen; Y. Rolain; F. Ferranti

doi:10.1049/el.2014.3649

Fast identification of Wiener-Hammerstein systems using discrete optimisation

M. Schoukens, G. Vandersteen, Y. Rolain, F. Ferranti

Research output: Contribution to journal › Article › Academic › peer-review

17 Citations (Scopus)

Abstract

A fast identification algorithm for Wiener-Hammerstein systems is proposed. The computational cost of separating the front and the back linear time-invariant (LTI) block dynamics is significantly improved by using discrete optimisation. The discrete optimisation is implemented as a genetic algorithm. Numerical results confirm the efficiency and accuracy of the proposed approach.

Original language	English
Pages (from-to)	1942-1944
Number of pages	3
Journal	Electronics Letters
Volume	50
Issue number	25
DOIs	https://doi.org/10.1049/el.2014.3649
Publication status	Published - 1 Jan 2014
Externally published	Yes

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10.1049/el.2014.3649

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abstract = "A fast identification algorithm for Wiener-Hammerstein systems is proposed. The computational cost of separating the front and the back linear time-invariant (LTI) block dynamics is significantly improved by using discrete optimisation. The discrete optimisation is implemented as a genetic algorithm. Numerical results confirm the efficiency and accuracy of the proposed approach.",

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AU - Rolain, Y.

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N2 - A fast identification algorithm for Wiener-Hammerstein systems is proposed. The computational cost of separating the front and the back linear time-invariant (LTI) block dynamics is significantly improved by using discrete optimisation. The discrete optimisation is implemented as a genetic algorithm. Numerical results confirm the efficiency and accuracy of the proposed approach.

AB - A fast identification algorithm for Wiener-Hammerstein systems is proposed. The computational cost of separating the front and the back linear time-invariant (LTI) block dynamics is significantly improved by using discrete optimisation. The discrete optimisation is implemented as a genetic algorithm. Numerical results confirm the efficiency and accuracy of the proposed approach.

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Fast identification of Wiener-Hammerstein systems using discrete optimisation

Abstract

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