Conference article

Using Modelica models in real time dynamic optimization - gradient computation

Pål Kittilsen
Cybernetica AS, Norway

Lars Imsland
Cybernetica AS, Norway

Tor Steinar Schei
Cybernetica AS, Norway

Download articlehttp://dx.doi.org/10.3384/ecp09430067

Published in: Proceedings of the 7th International Modelica Conference; Como; Italy; 20-22 September 2009

Linköping Electronic Conference Proceedings 43:88, s. 748-756

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Published: 2009-12-29

ISBN: 978-91-7393-513-5

ISSN: 1650-3686 (print), 1650-3740 (online)

Abstract

This paper reports on implementation of gradient computation for real-time dynamic optimization; where the dynamic models can be Modelica models. Analytical methods for gradient computation based on sensitivity integration is compared to finite difference-based methods. A case study reveals that analytical methods outperforms finite difference-methods as the number of inputs and/or input blocks increases.

Keywords

Nonlinear Model Predictive Control; Sequential Quadratic Programming; Gradient computation; Offshore Oil and Gas Production

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