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Least costly closed-loop performance diagnosis and plant re-identification
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0002-9368-3079
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2015 (English)In: International Journal of Control, ISSN 0020-7179, E-ISSN 1366-5820, Vol. 88, no 11, 2264-2276 p.Article in journal (Refereed) Published
Abstract [en]

The inherent time-varying nature of dynamics in chemical processes often limits the lifetime performance of model-based control systems, as the plant and disturbance dynamics change over time. A critical step in the maintenance of model-based controllers is distinguishing control-relevant plant changes from variations in disturbance characteristics. In this paper, prediction error identification is used to evaluate a hypothesis test that detects if the performance drop arises from control-relevant plant changes. The decision rule is assessed by verifying whether an identified model of the true plant lies outside the set of all plant models that lead to adequate closed-loop performance. A unified experiment design framework is presented in the least costly context (i.e., least intrusion of nominal plant operation) to address the problem of input signal design for performance diagnosis and plant re-identification when the performance drop is due to plant changes. The application of the presented performance diagnosis approach to a (nonlinear) chemical reactor demonstrates the effectiveness of the approach in detecting the cause of an observed closed-loop performance drop based on the designed least costly diagnosis experiment.

Place, publisher, year, edition, pages
Taylor & Francis, 2015. Vol. 88, no 11, 2264-2276 p.
Keyword [en]
closed-loop performance diagnosis, hypothesis testing, optimal experiment design, prediction error identification, Closed-loop performance, Diagnosis experiments, Model-based control systems, Model-based controller, Performance diagnosis, Prediction error identifications, Drops
National Category
Control Engineering
URN: urn:nbn:se:kth:diva-175036DOI: 10.1080/00207179.2015.1040076ISI: 000364315400008ScopusID: 2-s2.0-84947043668OAI: diva2:881664
EU, FP7, Seventh Framework Programme, 257059

QC 20151211

Available from: 2015-12-11 Created: 2015-10-09 Last updated: 2015-12-11Bibliographically approved

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Hjalmarsson, Håkan
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