Operational estimation and prediction of nitrification dynamics in the activated sludge process

Abstract This paper examines the feasibility and discusses the potential of applications of on-line real-time state estimation and prediction in operational control of the activated sludge process. In particular, the dynamics of nitrification are considered with reference to the activated sludge unit at the Norwich Sewage Works in eastern England. A recursive estimation algorithm, the extended Kalman filter, is applied both for reconstructing operating information on the variations in nitrifying bacterial population concentrations and for making predictions of process performance under assumed scenarios for the short-term future operating conditions of the plant. Time-series field data from the Norwich Works are used for the former analysis. Considerations of uncertainty and the possibility of rapid major perturbations in performance, for example, due to spillages of toxic substances or the loss of solids over the clarifier weir, are of special importance to the discussion. The paper is introduced and concluded with some more general comments on the roles of operator experience and decision-making and man-machine interaction in wastewater treatment plant control.

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