Experiment designs to minimize input peak and crest factor in MIMO system identification

A4 Conference proceedings

Internal Authors/Editors

Publication Details

List of Authors: Kurt E. Häggblom
Place: Piscataway, New Jersey, USA
Publication year: 2019
Publisher: IEEE
Book title: Proc. 2019 IEEE Conference on Control Technology and Applications (CCTA)
Start page: 499
End page: 504
ISBN: 978-1-7281-2767-5/19/


The quality of the data for system identification is of utmost of
importance. Ideally, the output data should satisfy requirements
regarding variance, and in the case of multiple-input multiple-output
(MIMO) systems, correlation between the outputs. Usually, it is desired
to achieve this by input perturbations with peak values as small as
possible. A related measure is the crest factor, which is a measure of
the (inverse) power of an input perturbation with given peak value. In
this paper, the effect of minimizing the input peak and the crest
factor, subject to desired output variances/covariances, is studied for
various types of perturbation signals. The design procedure is
completely data based; data are obtained by one or more preliminary
experiments with the system to be identified. A model of an
ill-conditioned distillation column is used for illustration.


data-based design, experiment design, ill-conditioned systems, multivariable systems, system identification

Last updated on 2020-18-02 at 05:53