Data Informativity for the Closed-Loop Identification of MISO ARX Systems
2021 (English)In: IFAC PAPERSONLINE, Elsevier BV , 2021, Vol. 54, no 7, p. 779-784Conference paper, Published paper (Refereed)
Abstract [en]
In the Prediction Error identification framework, it is crucial that the collected data are informative with respect to the chosen model structure to get a consistent estimate. In this work, we focus on the data informativity property for the identification of multi-inputs single-output ARX systems in closed-loop and we derive a necessary and sufficient condition to verify if a given multisine external excitation combined with the feedback introduced by the controller yields informative data with respect to the chosen model structure.
Place, publisher, year, edition, pages
Elsevier BV , 2021. Vol. 54, no 7, p. 779-784
Keywords [en]
System Identification, Data Informativity, Prediction Error Method, Consistency
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:kth:diva-303771DOI: 10.1016/j.ifacol.2021.08.456ISI: 000696396200129Scopus ID: 2-s2.0-85118188327OAI: oai:DiVA.org:kth-303771DiVA, id: diva2:1605342
Conference
19th IFAC Symposium on System Identification (SYSID), JUL 13-16, 2021, Padova, ITALY
Note
QC 20211022
2021-10-222021-10-222022-06-25Bibliographically approved