This paper addresses the forced periodic operation of a tubular reverse osmosis process for improved performance. The investigation is carried out through simulation of a previously validated model for the RO process. The feed pressure and feed flow rate are transformed into periodic behavior in the form of sinusoidal functions. A nonlinear model predictive control algorithm is utilized to regulate the amplitude and period of the sinusoidal functions that formulate the input signal. The control system managed to generate the cyclic inputs necessary to enhance the closed-loop performance in terms of higher permeate production and lower salt concentration. The proposed control algorithm can attain its objective with and without defining a set point for the controlled outputs. In the latter case, the process is driven to the best achievable performance. Similar successful results in terms of improved production and quality of water were also obtained in the presence of modeling errors and external disturbances. (C) 2011 Elsevier Ltd. All rights reserved.