Stabilizing control of a urine nitrification process in the presence of sensor drift

Abstract

Sensor drift is commonly observed across engineering disciplines, particularly in harsh media such as wastewater. In this study, a novel stabilizing controller for nitrification of high strength ammonia solutions is designed based on online signal derivatives. The controller uses the derivative of a drifting nitrite signal to determine if nitrite-oxidizing bacteria (NOB) are substrate limited or substrate inhibited. To ensure a meaningful interpretation of the derivative signal, the process is excited in a cyclic manner by repeatedly exposing the NOB to substrate-limited and substrate-inhibited conditions. The resulting control system successfully prevented nitrite accumulations for a period of 72 days in a laboratory-scale reactor. Slow disturbances in the form of feed composition changes and temperature changes were successfully handled by the controller while short-term temperature disturbances are shown to pose a challenge to the current version of this controller. Most importantly, we demonstrate that drift-tolerant control for the purpose of process stabilization can be achieved without sensor redundancy by combining deliberate input excitation, qualitative trend analysis, and coarse process knowledge.