Closed-loop identification with MPC for an industrial scale CD-control problem

An approach to implementing closed-loop identification in a model predictive-control framework for the cross-direction control of basis weight is proposed. The closed-loop-identification technique uses the concepts of Markov parameters to determine a step-response model that can then be used within a model predictive controller. The technique is applied to an industrial-scale paper-machine-simulation benchmark problem for cases of varying degrees of shrinkage. The performance of wet- and dry-end full-array sensors are compared. Also, the performance of the closed-loop identification is compared for a nominal case and two cases in which shrinkage occurs in the drying process.