@inproceedings{600c5a077abd412382f8f9a711e6e962,
title = "Data-Driven Modeling of a CO2 Refrigeration System",
abstract = "This paper describes a data-driven method for system identification of a CO2 refrigeration system. Traditionally, the interaction between the measured variables is not utilized as they are highly dependent on the refrigeration system. In this work a data-driven method, namely subspace identification, is investigated for deriving a control-oriented model such that the dynamic interaction in the refrigeration systems can be utilized for e.g. fault detection and diagnosis. The subspace identification is applied on laboratory data obtained from a test setup located at NTNU in Trondheim, Norway. The obtained results offer promising perspectives for performance improvement in fault detection and diagnosis methods as well as control strategies.",
author = "Glenn Andreasen and Jakob Stoustrup and Roozbeh Izadi-Zamanabadi and {{\'A}. Pardi{\~n}as}, {\'A}ngel and Armin Hafner",
year = "2019",
month = aug,
day = "29",
doi = "10.23919/ACC.2019.8814871",
language = "English",
isbn = "978-1-5386-7901-2",
series = "American Control Conference",
publisher = "IEEE",
pages = "5385--5390",
booktitle = "2019 American Control Conference (ACC)",
address = "United States",
note = "2019 American Control Conference (ACC) ; Conference date: 10-07-2019 Through 12-07-2019",
}