Learning Nonlinear Marine Predator Algorithm for Multi-objective Optimization of Setpoints in Wastewater Treatment Operations
The nitrogen removal in wastewater treatment plants (WWTPs) usually consumes a significant amount of energy, for example, oxygen injection. To reduce energy consumption while ensure the quality in the effluent of WWTPs, this paper proposes a control strategy based on the Multi-Objective Nonlinear Marine Predator Algorithm (MONMPA). First, to address the unacceptable energy consumption issue due to fixed setpoints in the wastewater treatment process, a multi-objective setpoint optimization scheme is proposed in this paper. Second, to deal with uncontrollable inflow disturbances and uncertainty, a predictive controller with feedforward compensation for inflow disturbances is adopted to further accurately track the optimized setpoints. Finally, the proposed control strategy is compared with other standard approaches, and experimental results showed the effectiveness and superiority of this strategy.
Authors
- Daoping Huang (ORCID: https://orcid.org/0000-0001-6232-4164)
- Jian-Guo Liu (ORCID: https://orcid.org/0000-0002-5641-0266)
- Yiqi Liu (ORCID: https://orcid.org/0000-0001-8911-727X)
Institutions
- South China University of Technology (CN)
Publication Details
- Published
- 2025-03-07
- DOI
- https://doi.org/10.1109/icrca64997.2025.11011048
- Primary Topic
- Metaheuristic Optimization Algorithms Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China