Dynamic plant-wide optimization of wastewater treatment plant performance using neuro-fuzzy models and predictive controlKarer, Gorazd (Avtor) Vrečko, Darko (Avtor) Hvala, Nadja (Avtor) Škrjanc, Igor (Avtor) multi-objective optimizationlong-term control evaluationneuro-fuzzy modelingmodel predictive controlwastewater treatment operationWastewater treatment plants (WWTPs) are complex facilities that must be operated efficiently from both environmental and economic perspectives. They need to balance a range of often conflicting performance objectives, necessitating a plant-wide approach and multi-objective optimization. This paper presents an approach for dynamic plant-wide optimization of the effluent quality index (EQI) and operational cost index (OCI) by employing reduced neuro-fuzzy models to represent performance indices, combined with simplified predictive control. The approach is validated through a one-year simulation using the plant-wide benchmark simulation model no. 2 (BSM2PSFe) and by dynamically optimizing the dissolved oxygen (DO) concentration set-point in an aerobic reactor. The Pareto front of optimal solutions is analyzed, and the individual indices are integrated into a single objective function by adjusting the weights of the criteria. The results show that the proposed optimization approach provides a better trade-off between the EQI and OCI indices than constant DO set-point values. Compared to the DO set-point of 1.5 g/m3 , the presented optimization case improves EQI for 2.64% and OCI for 0.87%. The advantage of the approach, apart from plant-wide consideration, is its reliance on measurements available in practice, making it suitable for implementation in real WWTPs.20262026-11-09 12:51:55Članek v reviji190966UDK: 681.5ISSN pri članku: 1944-3994DOI: 10.1016/j.dwt.2026.102008COBISS_ID: 304446979sl