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

A4 Konferenspublikationer


Interna författare/redaktörer


Publikationens författare: Mikael Manngård, Jari M. Böling, Hannu T. Toivonen
Redaktörer: Antonio Espuña, Moisès Graells, Luis Puigjaner
Publiceringsår: 2017
Förläggare: Elsevier
Moderpublikationens namn: 27th European Symposium on Computer Aided Process Engineering
Seriens namn: Computer Aided Chemical Engineering
Volym: 40
Artikelns första sida, sidnummer: 307
Artikelns sista sida, sidnummer: 312
ISBN: 978-0-444-63965-3
eISBN: 978-0-444-63970-7


Abstrakt

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.


Senast uppdaterad 2019-15-09 vid 06:17