Optimization of anoxic/oxic step feeding activated sludge process with fuzzy control model for improving nitrogen removal

It has been proved that higher total nitrogen removal efficiency could be obtained in step feeding activated sludge process by adjusting the inflow rate distribution and the volume of each stage. But the optimization of the step feeding process would be complicated owing to adjustment of inflow rate and volume. To develop the auto-control and operational decision support system is an urgent and necessary work for well application of step feeding process. Although biological wastewater treatment, especially the biological nitrogen removal process, has the characteristics of complex nonlinear, it provides widespread opportunities for artificial intelligent control. In this paper a fuzzy control model of anoxic/oxic step feeding activated sludge process was developed under the condition of sufficient and insufficient influent carbon source. The detailed information on development of fuzzy model was addressed based on collecting and analyzing previous experimental data. The influent C/N ratio was selected as input variable and inflow rate and volume distribution in each stage were selected as output variables. Moreover, the calibration and application approaches of control model were also studied through pilot-scale experiments (1000 L/d) with domestic sewage. The highlight is that the method and approach of model calibration are well discussed so that it provides good opportunities on practical application. During three months experimental period enhanced total nitrogen removal efficiency of more than 95.1% was reached with the influent C/N ratio of 8.16–12.3, average of 9.78.