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Autonomous maintenance of advanced process control: Application to an industrial depropanizer
KTH, School of Electrical Engineering (EES), Automatic Control.
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2014 (English)In: Fuels and Petrochemicals Division 2014 - Core Programming Area at the 2014 AIChE Spring Meeting and 10th Global Congress on Process Safety, Vol. 2, 923-932 p.Article in journal (Refereed) Published
Abstract [en]

Although Model Predictive Control (MPC) has been widely accepted as a main technology for Advanced Process Control (APC) due to its ability of operating the system closely to the constraints, proper maintenance of MPC systems is still a challenge. Based on this observation, this research aims to develop an automated support strategy for the autonomous maintenance of MPC. In this work, re-tuning and re-identification components of the automated support strategy are considered as corrective action to retain the performance of the system after a change in the plant dynamics causes performance degradation. An industrial FT-depropanizer is used to test the implementation of these components. Results successfully show that an automated unified framework approach to MPC maintenance can successfully be used in further securing the economic leverage of MPC in industry.

Place, publisher, year, edition, pages
2014. Vol. 2, 923-932 p.
Keyword [en]
Automation; Intelligent control; Maintenance; Predictive control systems, Advanced Process Control; Automated support; Corrective actions; Performance degradation; Plant dynamics; Re identifications; Re-tuning; Unified framework, Model predictive control
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
URN: urn:nbn:se:kth:diva-168126ScopusID: 2-s2.0-84912124826OAI: diva2:815676

QC 20150601

Available from: 2015-06-01 Created: 2015-05-27 Last updated: 2015-06-01Bibliographically approved

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Larsson, Christian
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