In this paper a model predictive controller (MPC) for ammonia nitrogen is presented and evaluated in a real activated sludge process. A reduced nonlinear mathematical model based on mass balances is used to model the ammonia nitrogen in the activated sludge plant. An MPC algorithm that minimises only the control error at the end of the prediction interval is applied. The results of the ammonia MPC were compared with the results of the ammonia feedforward-PI and ammonia PI controllers from our previous study. The ammonia MPC and ammonia feedforward-PI controller give better results in terms of ammonia removal and aeration energy consumption than the ammonia PI controller because of the measurable disturbances used. On the other hand, with the ammonia MPC, comparable or even slightly poorer results than with the ammonia feedforward-PI controller are obtained. Further improvements to the MPC could be possible with an improved accuracy of the nonlinear reduced model of the ammonia nitrogen, more sophisticated control criteria used inside the controller and the extension of the problem from univariable ammonia to multivariable total nitrogen control.
Keywords: activated sludge process, aeration control, ammonia control, model predictive control, oxygen control