“Model-Based Optimizing Control and Estimation Using Modelica Model”

Authors: Lars Imsland, Pål Kittilsen and Tor S. Schei,
Affiliation: NTNU, Department of Engineering Cybernetics
Reference: 2010, Vol 31, No 3, pp. 107-121.

Keywords: Non-linear model predictive control, state estimation, Modelica, offshore oil- and gas production, gradient computation

Abstract: 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.

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  title={{Model-Based Optimizing Control and Estimation Using Modelica Model}},
  author={Imsland, Lars and Kittilsen, Pål and Schei, Tor S.},
  journal={Modeling, Identification and Control},
  publisher={Norwegian Society of Automatic Control}