Subspace identification for MIMO systems in the presence of trends and outliers

A4 Conference proceedings


Internal Authors/Editors


Publication Details

List of Authors: Mikael Manngård, Jari M. Böling, Hannu T. Toivonen
Editors: Antonio Espuña, Moisès Graells, Luis Puigjaner
Publication year: 2017
Publisher: Elsevier
Book title: 27th European Symposium on Computer Aided Process Engineering
Title of series: Computer Aided Chemical Engineering
Volume number: 40
Start page: 307
End page: 312
ISBN: 978-0-444-63965-3
eISBN: 978-0-444-63970-7


Abstract

In this paper we present a framework for subspace identification of multiple-input multiple output linear time-invariant systems from data corrupted by outliers and piece-wise linear trends. The subspace identification problem is formulated as a sparsity constrained rank minimization problem that is relaxed using the nuclear norm and the l1-norm. The proposed identification method has been validated on a simulated example and on a case study using data from a pilot-plant distillation column.


Last updated on 2019-09-12 at 04:03