Evaluation of rule-based control strategies according to process state diagnosis in A2/O process

Abstract

In this study, rule-based control strategies were proposed according to the result of the process state diagnosis. Multivariate statistical techniques were used to derive the diagnosis results that included comprehensive information for the current process state. Based on the diagnosis result, the quantitative control setpoint could be calculated by using the optimized mathematical model. The developed process diagnosis procedure and the control strategies were applied in a pilot-scale A2/O (anaerobic/anoxic/oxic) process. The target variables in the proposed rule-based control strategies according to the process state diagnosis were the effluent NH4–N and NOX–N components. From the application of these rule-based control strategies according to the process state diagnosis, the percentages of groups 3 and 4, which were considered the abnormal process state, were decreased by about 53.8% compared to the no-control case. In addition, the maintenance interval of the control action ranged from 4h to 25h. Effluent NH4–N and NOX–N concentrations lower than the target values were maintained by applying the proposed rule-based control strategies according to the process state diagnosis. Moreover, frequent changes of the process operating state were minimized and the electrical equipment load was reduced.