Input design to maximize information for identification of MIMO systems

A4 Conference proceedings


Internal Authors/Editors


Publication Details

List of Authors: Kurt E. Häggblom
Place: Piscataway, NJ
Publication year: 2019
Publisher: IEEE
Book title: 2019 12th Asian control conference (ASCC)
Start page: 1323
End page: 1328
ISBN: 978-1-7281-0263-4
eISBN: 978-4-88898-300-6


Abstract

A new input design method for identification of multiple-input multiple-output (MIMO) systems is introduced. The method is completely data based as opposed to previous model-based methods. The data are obtained from one or more experiments with the system to be identified. These experiments do not require any MIMO input design. The design objective is to generate maximally informative data when a new experiment based on MIMO input design is done. The data are considered to be maximally informative when the outputs have maximal variance, subject to some constraints, and no correlation. Since the input design, with given type of perturbation signal, is not unique, it is possible to optimize some additional property, such as minimization of input or output peak value. The various design options are illustrated by application to a system with three inputs and three outputs.


Keywords

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

Last updated on 2020-19-09 at 05:35