Parametric MIMO parallel Wiener identification

Maarten Schoukens, Yves Rolain

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

6 Citations (Scopus)

Abstract

This paper proposes a parametric identification method for multi-input multi-output parallel Wiener systems. The linear dynamic parts of the system are modeled by a parametric rational function in the continuous or discrete time variable, while the static nonlinearities are represented by a linear combination of nonlinear basis functions. The identification method uses a three step procedure to obtain initial estimates. In the first step, the frequency response matrix of the best linear approximation is estimated for different input excitation levels. In the second step, the power dependent dynamics are decomposed over a number of parallel orthogonal branches. In the last step, the static nonlinearities are estimated using a linear least squares estimation. Finally both linear and nonlinear parameters are estimated together using a nonlinear optimization procedure. The method is illustrated on a simulation example.

Original languageEnglish
Title of host publication2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011
Place of PublicationPiscataway
Pages5100-5105
Number of pages6
DOIs
Publication statusPublished - 1 Dec 2011
Externally publishedYes
Event50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC 2011) - Hilton Orlando Bonnet Creek, Orlando, United States
Duration: 12 Dec 201115 Dec 2011
Conference number: 50
http://www.ieeecss.org/CAB/conferences/cdcecc2011/

Conference

Conference50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC 2011)
Abbreviated titleCDC-ECC 2011
Country/TerritoryUnited States
CityOrlando
Period12/12/1115/12/11
Other50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011
Internet address

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