On the significance of the noise model for the performance of a linear MPC in closed-loop operation

Morten Hagdrup, Dimitri Boiroux, Zeinab Mahmoudi, Henrik Madsen, Niels Kjølstad Poulsen, Bjarne Poulsen, John Bagterp Jørgensen

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Abstract

This paper discusses the significance of the noise model for the performance of a Model Predictive Controller when operating in closed-loop. The process model is parametrized as a continuous-time (CT) model and the relevant sampled-data filtering and control algorithms are developed. Using CT models typically means less parameters to identify. Systematic tuning of such controllers is discussed. Simulation studies are conducted for linear time-invariant systems showing that choosing a noise model of low order is beneficial for closed-loop performance. (C) 2016, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
Original languageEnglish
Title of host publicationIFAC-PapersOnLine
Volume49
PublisherElsevier
Publication date2016
Pages171-176
DOIs
Publication statusPublished - 2016
Event11th IFAC Symposium on Dynamics and Control of Process Systems Including Biosystems DYCOPS-CAB 2016 - Trondheim, Norway
Duration: 6 Jun 20168 Jun 2016
Conference number: 11
http://dycops2016.org/

Conference

Conference11th IFAC Symposium on Dynamics and Control of Process Systems Including Biosystems DYCOPS-CAB 2016
Number11
CountryNorway
CityTrondheim
Period06/06/201608/06/2016
Internet address
SeriesIFAC-PapersOnLine
ISSN2405-8963

Keywords

  • Closed-loop control predictive control
  • Model based control
  • Kalman Filters
  • State estimation

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