Abstract
The application of synthetic supercolloids extends across multiple industries. Owing to their unique rheology, there is an increasing demand for these products. Therefore, the large-scale production of these colloids must be efficiently done. Although some very new studies have shed light on the controlled production of these colloids, no studies have focused on the online estimation of system rheology during the production. Furthermore, it is desired to have accurate estimates of the process variables from only a few measurements. Hence, it is essential to design a proper soft sensor that can estimate the process states accurately with a few measurements. Motivated by these requirements, a moving horizon state-estimator (MHE) was designed in this work. Specifically, the MHE-based soft sensor was designed with a nonlinear model developed to relate the process inputs to the system rheology. Finally, the developed framework was implemented to a case study of wormlike micelles produced from cetrimonium bromide (CTAB) and sodium chloride (NaCl).
Original language | English |
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Pages (from-to) | 940-945 |
Number of pages | 6 |
Journal | IFAC-PapersOnLine |
Volume | 55 |
Issue number | 7 |
DOIs | |
State | Published - 2022 |
Event | 13th IFAC Symposium on Dynamics and Control of Process Systems, including Biosystems, DYCOPS 2022 - Busan, Korea, Republic of Duration: 14 Jun 2022 → 17 Jun 2022 |
Bibliographical note
Publisher Copyright:© 2022 Elsevier B.V.. All rights reserved.
Keywords
- Soft sensor
- colloids
- moving horizon state-estimator (MHE)
- rheology
- wormlike micelles (WLMs)