“Model-Free Predictive Anti-Slug Control of a Well-Pipeline-Riser”
Authors: Christer Dalen and David Di Ruscio,Affiliation: Telemark University College
Reference: 2016, Vol 37, No 1, pp. 41-52.
Keywords: Model-Free, Model Predictive Control, Kalman filter, system identification, anti-slug, well-pipeline-riser
Abstract: Simplified linearized discrete time dynamic state space models are developed for a 3-phase well-pipeline-riser and tested together with a high fidelity dynamic model built in K-Spice and LedaFlow. In addition the Meglio pipeline-riser model is used as an example process. These models are developed from a subspace algorithm, i.e. Deterministic and Stochastic system identification and Realization (DSR), and implemented in a Model Predictive Controller (MPC) for stabilizing the slugging regime. The MPC, LQR and PI control strategies are tested.
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DOI: 10.4173/mic.2016.1.4DOI forward links to this article:
| [1] Christer Dalen and David Di Ruscio (2019), doi:10.4173/mic.2019.4.2 |
[1] Akaike, H. (1974). Akaike, H, A new look at the statistical model identification. Automatic Control, IEEE Transactions on. 19(6):716--723. doi:10.1109/TAC.1974.1100705
[2] Courbot, A. (1996). Courbot, A, Prevention of Severe Slugging in the Dunbar 16' Multiphase Pipeline. Proc. Annual Offshore Technology Conference. doi:10.4043/8196-MS
[3] Dalen, C., DiRuscio, D., and Nilsen, R. (2015). Dalen, C, , DiRuscio, D., and Nilsen, R. Model-free optimal anti-slug control of a well-pipeline-riser in the K-Spice/LedaFlow simulator. Modeling, Identification and Control. 36(3):179--188. doi:10.4173/mic.2015.3.5
[4] DiMeglio, F., Kaasa, G., Petit, N., and Alstad, V. (2010). DiMeglio, F, , Kaasa, G., Petit, N., and Alstad, V. Model-based control of slugging flow: An experimental case study. In American Control Conference (ACC), 2010. pages 2995--3002, 2010. doi:10.1109/ACC.2010.5531271
[5] DiMeglio, F., Kaasa, G.-O., and Petit, N. (2009). DiMeglio, F, , Kaasa, G.-O., and Petit, N. A first principle model for multiphase slugging flow in vertical risers. In Decision and Control, 2009 held jointly with the 2009 28th Chinese Control Conference. CDC/CCC 2009. Proceedings of the 48th IEEE Conference on. pages 8244--8251. doi:10.1109/CDC.2009.5400680
[6] DiMeglio, F., Kaasa, G.-O., Petit, N., and Alstad, V. (2010). DiMeglio, F, , Kaasa, G.-O., Petit, N., and Alstad, V. Reproducing slugging oscillations of a real oil well. In Decision and Control (CDC), 2010 49th IEEE Conference on. pages 4473--4479, 2010. doi:10.1109/CDC.2010.5717367
[7] DiRuscio, D. (1996). DiRuscio, D, Combined Deterministic and Stochastic System Identification and Realization: DSR - A Subspace Approach Based on Observations. Modeling, Identification and Control. 17(3):193--230. doi:10.4173/mic.1996.3.3
[8] DiRuscio, D. (2013). DiRuscio, D, Model Predictive Control with Integral Action: A simple MPC algorithm. Modeling, Identification and Control. 34(3):119--129. doi:10.4173/mic.2013.3.2
[9] Favoreel, W., Moor, B.D., Gevers, M., and Overschee, P.V. (1999). Favoreel, W, , Moor, B.D., Gevers, M., and Overschee, P.V. Closed-loop model-free subspace-based LQG-design. in Proc. of the 7th Mediteranean Conference on Control and Automation (MED99), Haifa, Isreal. pages 1926 -- 1939. ftp://ftp.esat.kuleuven.be/pub/sista/ida/reports/98-107.pdf. .
[10] Godhavn, J.-M., Fard, M.P., and Fuchs, P.H. (2005). Godhavn, J, -M., Fard, M.P., and Fuchs, P.H. New slug control strategies, tuning rules and experimental results. Journal of Process Control. 15(5):547 -- 557. doi:http://dx.doi.org/10.1016/j.jprocont.2004.10.003
[11] Jahanshahi, E. and Skogestad, S. (2013). Jahanshahi, E, and Skogestad, S. Simplified dynamical models for control of severe slugging in multiphase risers. 18th IFAC World Congress. 36(3):233--240. doi:10.3182/20110828-6-IT-1002.00981
[12] Jahanshahi, E. and Skogestad, S. (2015). Jahanshahi, E, and Skogestad, S. Anti-slug control solutions based on identified model. Journal of Process Control. 30(0):58 -- 68. CAB/DYCOPS 2013 Selected Papers From Two Joint IFAC Conferences: 9th International Symposium on Dynamics and Control of Process Systems and the 11th International Symposium on Computer Applications in Biotechnology, Leuven, Belgium, July 5-9, 2010. doi:10.1016/j.jprocont.2014.12.007
[13] K-Spice. (2015). K-Spice, K-Spice version 3.2. 2015. kongsberg.com/k-spice. .
[14] LedaFlow. (2015). LedaFlow, LedaFlow version 1.7. 2015. kongsberg.com/ledaflow. .
[15] Ljung, L. (2007). Ljung, L, System identification toolbox for use with MATLAB. 2007. .
[16] OgaziAI, Y. H. . L.L., CaoY. (2010). OgaziAI, Y, H. . L.L., CaoY. Slug control with large valve openings to maximize oil production. SPE Journal. 15(3):812--821. doi:10.2118/124883-PA
[17] SchmidtZ., J. P. .B., Brill. (1979). SchmidtZ, , J. P. .B., Brill. Choking can eliminate severe pipeline slugging. Oil & Gas J. 312:230--238. .
[18] Storkaas, E. and Skogestad, S. (2003). Storkaas, E, and Skogestad, S. Cascade control of unstable systems with application to stabilization of slug flow. AdChem, Hong Kong, 2003. .
[19] Storkaas, E. and Skogestad, S. (2003). Storkaas, E, and Skogestad, S. A low-dimensional dynamic model of severe slugging for control design and analysis. 2003. 11th International Conference on Multiphase flow (Multiphase '03). .
BibTeX:
@article{MIC-2016-1-4,
title={{Model-Free Predictive Anti-Slug Control of a Well-Pipeline-Riser}},
author={Dalen, Christer and Di Ruscio, David},
journal={Modeling, Identification and Control},
volume={37},
number={1},
pages={41--52},
year={2016},
doi={10.4173/mic.2016.1.4},
publisher={Norwegian Society of Automatic Control}
};