Model-Based Optimizing Control and Estimation Using Modelica Model

This paper reports on experiences from case studies in using Modelica/Dymola models interfaced to control and optimization software, as process models in real time process control applications. Possible applications of the integrated models are in state- and parameter estimation and nonlinear model...

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Bibliographic Details
Published in:Modeling, identification and control identification and control, 2010-07, Vol.31 (3), p.107-121
Main Authors: Imsland, Lars, Kittilsen, Pål, Schei, Tor S
Format: Article
Language:English
Subjects:
Modelica
Non-linear model predictive control
offshore oil- and gas production
state estimation
Online Access:Get full text
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Summary:This paper reports on experiences from case studies in using Modelica/Dymola models interfaced to control and optimization software, as process models in real time process control applications. Possible applications of the integrated models are in state- and parameter estimation and nonlinear model predictive control. It was found that this approach is clearly possible, providing many advantages over modeling in low-level programming languages. However, some effort is required in making the Modelica models accessible to NMPC software.
ISSN:0332-7353
1890-1328
DOI:10.4173/mic.2010.3.3