Biological nitrogen removal in aerobic granular sequencing batch reactors is sensitively affected by process conditions (e.g. dissolved oxygen (DO) concentration, nitrogen loading rate (NLR), influent C/N ratio, among others). The variation of one of these process conditions affects the others, because often they are tightly linked. These interrelationships are a drawback for the experimental assessment of the target domain of process conditions required to enhance N-removal. Here, we have developed a model to determine the guidelines to design an automatic control strategy with the final aim of enhancing biological N-removal in a granular sequencing batch reactor. The model was first calibrated with experimental data from a granular sequencing batch reactor treating