Experiments in a pilot-scale fixed-bed reactor system have been conducted to obtain the process input-output data for the titanium-based zeolite-catalyzed hydroxylation of phenol to dihydroxybenzenes. An artificial neural-network-based strategy has been used for identifying the process model covering the range of experimental conditions. The identified neural network model has been used to design a model predictive controller that has been tested on the experimental rig.