Bibliographic Details
| Title: |
Design of a stable adaptive controller for driving aerobic fermentation processes near maximum oxygen transfer capacity |
| Authors: |
Oliveira, R.1 rui.oliveira@dq.fct.unl.pt, Simutis, R.2, Feyo de Azevedo, S.3 |
| Source: |
Journal of Process Control. Sep2004, Vol. 14 Issue 6, p617. 10p. |
| Subjects: |
Fermentation, Oxygen, Industrial efficiency, Production (Economic theory) |
| Abstract: |
In many industrial fermentation processes oxygen availability is the main limiting factor for product production. Typically the dissolved oxygen (DO) concentration decreases continuously at the beginning of the batch until it reaches a critical level where the oxygen transfer rate is very close to the vessel''s maximum transfer capacity. The process may be further driven close to this sensitive operating point with a controller that manipulates the carbon source feed rate. This operating strategy is linked with important productivity issues and is still frequently realised in open-loop at production scale. The main purpose of the present study is to derive an effective closed-loop control solution and to demonstrate its economical advantage in relation to the open-loop form of operation. A stable model reference adaptive controller (MRAC) was designed based on a phenomenological model of the process. The implementation requires two on-line measurements: the DO tension and oxygen transfer rate (OTR) between gas–liquid phases, which are nowadays standard and easily available in production facilities. The controller performance is accessed with a simulation case study. The main results show that the adaptive controller is precise, stable and robust to disturbances and to inaccuracies like variability in raw materials typical in fermentations run in complex media. The controller is simple, easy to implement, and could possibly improve productivity in processes for which oxygen transfer capacity is limiting growth and product production. [Copyright &y& Elsevier] |
|
Copyright of Journal of Process Control is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Database: |
Engineering Source |