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Li D, Zou M, Jiang L. Dissolved oxygen control strategies for water treatment: a review. WATER SCIENCE AND TECHNOLOGY : A JOURNAL OF THE INTERNATIONAL ASSOCIATION ON WATER POLLUTION RESEARCH 2022; 86:1444-1466. [PMID: 36178816 DOI: 10.2166/wst.2022.281] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Dissolved oxygen (DO) is one of the most important water quality factors. Maintaining the DO concentration at a desired level is of great value to both wastewater treatment plants (WWTPs) and aquaculture. This review covers various DO control strategies proposed by researchers around the world in the past 20 years. The review focuses on published research related to determination and control of DO concentrations in WWTPs in order to improve control accuracy, save aeration energy, improve effluent quality, and achieve nitrogen removal. The strategies used for DO control are categorized and discussed through the following classification: classical control such as proportional-integral-derivative (PID) control, advanced control such as model-based predictive control, intelligent control such as fuzzy and neural networks, and hybrid control. The review also includes the prediction and control strategies of DO concentration in aquaculture. Finally, a critical discussion on DO control is provided. Only a few advanced DO control strategies have achieved successful implementation, while PID controllers are still the most widely used and effective controllers in engineering practice. The challenges and limitations for a broader implementation of the advanced control strategies are analyzed and discussed.
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Affiliation(s)
- Daoliang Li
- National Innovation Center for Digital Fishery, China Agricultural University, Beijing 100083, China E-mail: ; Key Laboratory of Smart Farming Technologies for Aquatic Animal and Livestock, Ministry of Agriculture and Rural Affairs, Beijing 100083, China; Beijing Engineering and Technology Research Centre for Internet of Things in Agriculture, China Agricultural University, Beijing 100083, China; College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
| | - Mi Zou
- National Innovation Center for Digital Fishery, China Agricultural University, Beijing 100083, China E-mail: ; Key Laboratory of Smart Farming Technologies for Aquatic Animal and Livestock, Ministry of Agriculture and Rural Affairs, Beijing 100083, China; Beijing Engineering and Technology Research Centre for Internet of Things in Agriculture, China Agricultural University, Beijing 100083, China; College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
| | - Lingwei Jiang
- National Innovation Center for Digital Fishery, China Agricultural University, Beijing 100083, China E-mail: ; Key Laboratory of Smart Farming Technologies for Aquatic Animal and Livestock, Ministry of Agriculture and Rural Affairs, Beijing 100083, China; Beijing Engineering and Technology Research Centre for Internet of Things in Agriculture, China Agricultural University, Beijing 100083, China; College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
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Special Issue: Mathematical Modeling and Control of Bioprocesses. Processes (Basel) 2022. [DOI: 10.3390/pr10071372] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/10/2022] Open
Abstract
This Special Issue (SI) of Processes on Mathematical Modeling and Control of Bioprocesses (MMCB) contains papers focusing, on the one hand, on mathematical modeling of biological processes at different scales ranging from microscopic to macroscopic levels and, on the other hand, on model-based estimation, optimization and control of these processes [...]
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