Abstract
Presented research relates to control of dissolved oxygen in a bioreactor. There were assumed a nonlinear relation between the volumetric oxygen transfer coefficient and air flow into the reactor. Thus the volumetric oxygen transfer coefficient was assumed as a substitute of manipulated value. Two control algorithms were considered for oxygen stabilization: classical PI and model predictive one - PFC. Both algorithms were tested with simulated plant and as a conclusion selective control concept for stabilizing dissolved oxygen concentration in bioreactor is proposed. One of the strongest disturbances is a change of nutrients load, while considering the wastewater treatment activated sludge. That change causes variations in oxygen consumption and in result destabilizes desired level of oxygen concentration. Thus for correct performance of model base controller, an estimation on-line procedure was applied.
| Original language | English |
|---|---|
| Title of host publication | 2015 20th International Conference on Methods and Models in Automation and Robotics, MMAR 2015 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 602-607 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781479987016 |
| DOIs | |
| Publication status | Published - 29 Sept 2015 |
| Event | 20th International Conference on Methods and Models in Automation and Robotics, MMAR 2015 - Miedzyzdroje, Poland Duration: 24 Aug 2015 → 27 Aug 2015 |
Publication series
| Name | 2015 20th International Conference on Methods and Models in Automation and Robotics, MMAR 2015 |
|---|
Conference
| Conference | 20th International Conference on Methods and Models in Automation and Robotics, MMAR 2015 |
|---|---|
| Country/Territory | Poland |
| City | Miedzyzdroje |
| Period | 24/08/15 → 27/08/15 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 6 Clean Water and Sanitation
Keywords
- bioreactor control
- dissolved oxygene control
- predictive control
- selective contro
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Vision and Pattern Recognition
- Control and Systems Engineering
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