%0 Journal Article
%T Model-Based Optimizing Control and Estimation Using Modelica Model
%A L. Imsland
%A P. Kittilsen
%A T.S. Schei
%J Modeling, Identification and Control
%D 2010
%I Norwegian Society of Automatic Control
%R 10.4173/mic.2010.3.3
%X 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.
%K Non-linear model predictive control
%K state estimation
%K Modelica
%K offshore oil- and gas production
%U http://www.mic-journal.no/PDF/2010/MIC-2010-3-3.pdf