A nonlinear model predictive controller based on neural networks is designed in this paper to regulate the nitrogen removal in the activated-sludge process. The benchmark simulation model (BSM1) is used to implement the predictive controller and to study its behavior in different situations. Also input-output data are gathered from the benchmark for the neural networks training. Control results under dry-weather perturbations are satisfactory when compared to other types of NLMPC.