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


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 2020-04-07 vid 05:00