Control of a gas-liquid inline swirl separator based on tomographic measurements

Journal Article (2020)
Author(s)

M. M. Garcia (TU Delft - Applied Sciences)

B. Sahovic (Helmholtz Zentrum Dresden Rossendorf)

M. A. Sattar (Lodz University of Technology)

H. Atmani (Université de Toulouse)

E. Schleicher (Helmholtz Zentrum Dresden Rossendorf)

U. Hampel (Helmholtz Zentrum Dresden Rossendorf)

L. Babout (Lodz University of Technology)

D. Legendre (Université de Toulouse)

L. M. Portela (TU Delft - Applied Sciences)

Research Group
ChemE/Transport Phenomena
DOI related publication
https://doi.org/10.1016/j.ifacol.2020.12.588 Final published version
More Info
expand_more
Publication Year
2020
Language
English
Research Group
ChemE/Transport Phenomena
Issue number
2
Volume number
53
Pages (from-to)
11483-11490
Event
21st IFAC World Congress 2020 (2020-07-12 - 2020-07-17), Berlin, Germany
Downloads counter
314
Collections
Institutional Repository
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

This text structures the application of Wire-Mesh sensors and Electrical Resistance Tomography in the control of an Inline Swirl Separator. It introduces a mechanistic model of the two-phase flow inside the device, which is linearized around an ideal perfect operation, and implemented in a Model Predictive Controller. The whole text is structured aiming at a future real application of the controller, briefly introducing the setup that is going to be used, the sensors and their working principles. The results obtained show a stable controller, able to regulate the process relatively fast in relation to the time resolution of the sensors. The positive response of the approach stimulates further improvements in the model developed, and the implementation of more sophisticated techniques to handle the non-linearities of the process.