Sheet and film processes are prevalent in the chemical and pulp and paper industries, and include paper coating, polymer film extrusion, and papermaking. A model predictive control algorithm is developed which is based on an off-line singular value decomposition of the plant. The input constraints are approximated by an ellipsoid whose size is optimized online to reduce conservatism. The controller has a structure proven to be robust to model inaccuracies and is computationally efficient enough for real-time implementation on large scale sheet and film processes (e.g., manipulated variable settings computed for 200 actuators in less than ten CPU seconds). The algorithm is applied to a paper machine model constructed from industrial data.