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A PREDICTIVE CONTROL ALGORITHM FOR AN ACTIVATED SLUDGE TREATMENT PROCESS

The activated sludge process is a commonly used method for treating sewage and wastewaters. The main difficulty in controlling this kind of processes comes from the variability of kinetics parameters, the large variations in the hydraulic and organic input load and the limited amount of on-line information. This paper focuses on the development of a simple predictive control algorithm, used to control the effluent quality of an activated sludge treatment process. The activated sludge process considered in this study consists of an aeration tank and a settler/clarifier. It is assumed that the hydraulic characteristics of the aeration tank are approximate to those of a continuously stirred tank reactor. No biochemical reaction takes place in the settler. The control strategy, derived from the Generalized Predictive Control (GPC) is based on a linear incremental second order model with variable dead time and parameters. Those are estimated on-line by a recursive least square identification method, with a forgetting time factor and a constant sensitivity. The model is employed to predict the effluent pollution over a finite horizon, using an iterative method. This control model has the advantage of taking into account the main disturbances, which are respectively the inflow rate, and the incoming pollution concentration. The control inputs are computed from the predictions and the desired output set point. The simulations conducted under the Matlab® programming environment have shown that such a control strategy could improve the process performances by minimizing the effluent pollution and the energetic cost of the system.