Adaptive optimization of a nitrifying sequencing batch reactor

Although substantial research effort has been expended towards the modeling of nitrification process, optimization and control of nitrifying systems, especially using a sequencing batch reactor (SBR) configuration, is still lacking appropriate consideration. The present work addresses the problem of minimizing the cost of nitrification, using an on-line adaptive optimization algorithm. The algorithm is based on the on-line identification of the batch cycle duration and is used for the on-line determination of the fraction of switching period to be implemented. The performance of the algorithm was tested against a simplified nitrification model adopted from the activated sludge model No. 2 (ASM2). The convergence of the algorithm to the optimum fraction of switching period, as well as its ability to satisfactorily handle disturbances in the influent ammonium-nitrogen concentration, is demonstrated.