ARTICLE TITLE : Latent Variable Model Predictive Control (LV-MPC) for trajectory tracking in batch processes
Publication year: 2010
Source: Journal of Process Control, In Press, Corrected Proof, Available online 17 March 2010</br>
Masoud, Golshan , John F., MacGregor , Mark-John, Bruwer , Prashant, Mhaskar</br>
Latent Variable Model Predictive Control (LV-MPC) algorithms are developed for trajectory tracking and disturbance rejection in batch processes. The algorithms are based on multi-phase PCA models developed using batch-wise unfolding of batch data arrays. Two LV-MPC formulations are presented, one based on optimization in the latent variable space and the other on direct optimization over a finite vector of future manipulated variables. In both cases prediction of the future trajectories is accomplished using statistical latent variable missing data imputation methods. The proposed LV-MPCs can handle constraints. Furthermore, due to the batch-wise unfolding approach selected in the modeling section, the nonlinear...</br>


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