Since the beginning of collaboration with the sugar industry in 1989, the objective has been the improvement of manufacturing
processes to achieve optimal operating conditions. The present paper deals with the non-linear modelling of multiple-eect evaporation
in the cane sugar industry, with the aim of robust control. To overcome the limits of the traditional control systems, a
model-based predictive control (MPC) scheme was designed. As this control strategy requires the development of a predictive
model, a multistep ahead predictor neural network (NN) model of the plant was used. The test of the identi®ed NN models in
generalisation, and the simulation of the MPC scheme, on the basis of experimental data collected during several measurement
campaigns at the Bois Rouge sugar mill, illustrate the good performances of this new approach, showing promises for an on-line
implementation in the year 2000. Ó 2000 Elsevier Science Ltd. All rights reserved.