Modeling and Dynamic Parameterized Predictive Control of Dissolved Oxygen in Dual−Tank Bioreactor Systems
Muhang Li, Ran Tang, Yifei Li, Junning Cui

TL;DR
This paper introduces a new control method for managing dissolved oxygen in bioreactors, improving accuracy and response time compared to traditional approaches.
Contribution
A dynamic parameterized predictive control method is proposed for dissolved oxygen regulation in dual-tank bioreactors.
Findings
The model achieved an RMSE below 0.05 and an R2 exceeding 0.99 in experiments.
The method reduced ISE by 47.8% and IAE by 41.4% compared to conventional feedback control.
The controller rapidly restores DO levels with minimal overshoot and latency.
Abstract
Uneven distribution and delayed system response of dissolved oxygen (DO) in dual−tank recirculating bioreactor systems pose significant challenges for oxygen supply. To address these issues, a dynamic parameterized predictive control (DPPC) approach is proposed and validated through simulation and bench−scale experiments. This method is underpinned by a mathematical model that integrates mass transfer kinetics and chemical thermodynamic principles, accurately capturing oxygen dissolution and transfer within a recirculating environment. By predicting future DO variations and continuously integrating real−time monitoring data, the controller adjusts oxygen injection parameters in real time, rapidly restoring DO levels to target values while minimizing overshoot and latency introduced by system circulation. Experimental results in dual−tank setups show an RMSE below 0.05 and an R2…
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Taxonomy
TopicsWastewater Treatment and Nitrogen Removal · Advanced Control Systems Optimization · 3D Printing in Biomedical Research
