Data Driven Fault Detection with Robustness to Uncertain Parameters Identified in Closed Loop
2010 (English)In: Proceedings of the 49th IEEE Conference on Decision and Control, 2010, 750-755 p.Conference paper (Refereed)
This paper presents a new robustified data-driven fault detection approach, connected to closed-loop subspace identification. Although data-driven detection methods have recently been reported in the literature, attention has not yet been given to a robust solution coping with identification errors. The key idea of this paper is to analytically quantify the effect of the identification errors on the residual generator of a new data-driven detection approach, namely FICSI. The comparisons of the proposed robust FICSI detection scheme with both its nominal counterpart and the nominal data-driven PSA solutions have verified the effectiveness of accounting the identification errors in improving the performance of the data-driven detection scheme.
Place, publisher, year, edition, pages
2010. 750-755 p.
Closed loop systems, Fault diagnosis, Identification
IdentifiersURN: urn:nbn:se:liu:diva-95580DOI: 10.1109/CDC.2010.5718040ISBN: 978-1-4244-7745-6OAI: oai:DiVA.org:liu-95580DiVA: diva2:636214
49th IEEE Conference on Decision and Control, Atlanta, GA, USA, 15-17 December, 2010