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Simultaneous removal of nitrogen and phosphorous is a recommended practice while treating wastewater. In the present study, control strategies based on proportional-integral (PI), model predictive control (MPC), and fuzzy logic are developed and implemented on a plant-wide wastewater treatment plant. Four combinations of control frameworks are developed in order to reduce the operational cost and improve the effluent quality. As a working platform, a Benchmark simulation model (BSM2-P) is used. A default control framework with PI controllers is used to control nitrate and dissolved oxygen (DO) by manipulating the internal recycle and oxygen mass transfer coefficient (KLa). Hierarchical control topology is proposed in which a lower-level control framework with PI controllers is implemented to DO in the sixth reactor by regulating the KLa of the fifth, sixth, and seventh reactors, and fuzzy and MPC are used at the supervisory level. This supervisory level considers the ammonia in the last aerobic reactor as a feedback signal to alter the DO set-points. PI-fuzzy showed improved effluent quality by 21.1%, total phosphorus removal rate by 33.3% with an increase of operational cost, and a slight increase in the production rates of greenhouse gases. In all the control design frameworks, a trade-off is observed between operational cost and effluent quality.

Model predictive control (MPC) and Fuzzy controllers are designed in a two‐level hierarchical supervisory control framework for control of activated sludge‐based wastewater treatment plants (WWTP) in order to efficiently remove nitrogen and phosphorus. Benchmark simulation model No.3 with a bio‐phosphorus (ASM3bioP) module is used as a working platform. The hierarchical control framework is used to alter the dissolved oxygen in the seventh reactor (DO7) to control ammonia. Lower‐level PI, MPC, and Fuzzy are used to control the nitrate levels in the fourth reactor (SNO4) by manipulating internal recycle (Qintr) and DO7 in the seventh tank by manipulating mass transfer coefficient (KLa7). MPC and Fuzzy are designed in the supervisory layer to alter the DO7 set‐point based on the ammonia composition in the seventh reactor (NH7). From the analysis, it is observed that the effluent quality is improved with a decrease in ammonia, TN, and TP. Though a little difference was observed in the cost for all the control strategies, a trade‐off is maintained between cost and percentage improvement of effluent quality. MPC‐MPC combination showed significant removal in ammonia and better effluent quality when compared to other control strategies. Practitioner points Developed novel strategies in hierarchical configurations for better nutrient removal with optimal costs in an A2O process. Lower level control strategies deals with dissolved oxygen in last aeration tank and nitrate in fourth anoxic tank (PI/MPC) Higher level control strategy deals with ammonia in the last aeration tank (MPC/Fuzzy). Average and violations of nutrient removal, economy and overall effluent quality for three weather conditions (Dry, Rain and Strom) are studied. A trade‐off is observed between EQI and OCI.

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