Supervisory control system to enhance partial nitrification in an activated sludge reactor

This work proposes a supervisory control system based on an optimization layer to calculate the optimum pH and dissolved oxygen (DO) set-points for the SISO controller, maintaining the process at stable partial nitrification. Takagi–Sugeno fuzzy multimodels were implemented to estimate ammonium degradation and nitrite accumulation from on-line DO and pH values, and updated using off-line measurements. An activated sludge reactor was operated successfully over 115 consecutive days with the supervisory control system, achieving ammonium degradation and nitrite accumulation values higher than 95% and 80%, respectively. The on-line estimates of the multimodels showed a prediction error of less than 7% at steady state operation, and reflected the tendencies shown in experiment to be caused by changes in pH value and DO concentration.