Model Order Reduction for Managed Pressure Drilling Systems based on a model with local nonlinearities

Journal Article (2018)
Author(s)

S. Naderi Lordejani (Eindhoven University of Technology)

B Besselink (Rijksuniversiteit Groningen)

M. H. Abbasi (Eindhoven University of Technology)

G. O. Kaasa (Kelda Drilling Controls)

W.H.A. Schilders (Eindhoven University of Technology)

N. Wouw (TU Delft - Team Bart De Schutter, Eindhoven University of Technology, University of Minnesota Twin Cities)

Research Group
Team Bart De Schutter
Copyright
© 2018 S. Naderi Lordejani, B. Besselink, M. H. Abbasi, G. O. Kaasa, W. H.A. Schilders, N. van de Wouw
DOI related publication
https://doi.org/10.1016/j.ifacol.2018.06.354
More Info
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Publication Year
2018
Language
English
Copyright
© 2018 S. Naderi Lordejani, B. Besselink, M. H. Abbasi, G. O. Kaasa, W. H.A. Schilders, N. van de Wouw
Research Group
Team Bart De Schutter
Issue number
8
Volume number
51
Pages (from-to)
50-55
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Abstract

Automated Managed Pressure Drilling (MPD) is a method for fast and accurate pressure control in drilling operations. The achievable performance of automated MPD is limited, firstly, by the control system and, secondly, by the hydraulics model based on which this control system is designed. Hence, an accurate hydraulics model is needed that, at the same time, is simple enough to allow for the use of high performance controller design methods. This paper presents an approach for nonlinear Model Order Reduction (MOR) for MPD systems. For a single-phase flow MPD system, a nonlinear model is derived that can be decomposed into a feedback interconnection of a high-order linear subsystem and low-order nonlinear subsystem. This structure, under certain conditions, allows for a nonlinear MOR procedure that preserves key system properties such as stability and provides a computable error bound. The effectiveness of this MOR method for MPD systems is illustrated through simulations.

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