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Experimental evaluation of model predictive control with excitation (MPC-X) on an industrial depropanizer
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0003-0355-2663
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0002-9368-3079
2015 (English)In: Journal of Process Control, ISSN 0959-1524, E-ISSN 1873-2771, Vol. 31, 1-16 p.Article in journal (Refereed) Published
Abstract [en]

It is commonly observed that over the lifetime of most model predictive controllers, the achieved performance degrades over time. This effect can often be attributed to the fact that the dynamics of the controlled plant change as the plant ages, due to wear and tear, refurbishment and design changes of the plant, to name a few factors. These changes mean that re-identification is necessary to restore the desired performance of the controller. An extension of existing predictive controllers, capable of producing signals suitable for closed loop re-identification, is presented in this article. The main contribution is an extensive experimental evaluation of the proposed controller for closed loop re-identification on an industrial depropanizer distillation column in simulations and in real experiments. The plant experiments are conducted on the depropanizer during normal plant operations. In the simulations, as well as in the experiments, the updated models from closed loop re-identification result in improvement of the performance. The algorithm used combines regular model predictive control with ideas from applications oriented input design and linear matrix inequality based convex relaxation techniques. Even though the experiments show promising result, some implementation problems arise and are discussed.

Place, publisher, year, edition, pages
2015. Vol. 31, 1-16 p.
Keyword [en]
Closed-loop identification, Distillation column, Dual control, Experiment design, Industrial application, Model predictive control, Design, Distillation, Distillation columns, Identification (control systems), Industrial applications, Linear matrix inequalities, Predictive control systems, Relaxation processes, Closed loop identification, Convex relaxation, Experimental evaluation, Model predictive controllers, Predictive controller, Re identifications, Controllers
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:kth:diva-167698DOI: 10.1016/j.jprocont.2015.03.011Scopus ID: 2-s2.0-84927941340OAI: oai:DiVA.org:kth-167698DiVA: diva2:816033
Note

QC 20150602

Available from: 2015-06-02 Created: 2015-05-22 Last updated: 2017-12-04Bibliographically approved

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Rojas, Cristián R.Hjalmarsson, Håkan

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Larsson, Christian A.Rojas, Cristián R.Hjalmarsson, Håkan
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