Title :
Latent Variable MPC for trajectory tracking in batch processes: Role of the model structure
Author :
Golshan, Masoud ; MacGregor, John F. ; Bruwer, Mark-John ; Mhaskar, Prashant
Author_Institution :
Dept. of Chem. Eng., Mcmaster Univ., Hamilton, ON, Canada
Abstract :
The multiphase latent variable model predictive control (MLV-MPC) is developed based on the principal component analysis (PCA) model. The proposed control methodology is capable of trajectory tracking as well as disturbance rejection. The model that is used in the course of MPC is a multiphase PCA model that is constructed based on the available data from the measurements on the process. Different data arrangements are studied and their effects on the performance of the control algorithm are evaluated.
Keywords :
batch processing (industrial); position control; predictive control; principal component analysis; process control; tracking; batch process; latent variable MLV-MPC model; model predictive control; multiphase PCA model; multiphase latent variable; principal component analysis; trajectory tracking; Convergence; Helium; Monitoring; Mood; Predictive control; Predictive models; Principal component analysis; Process control; Trajectory; Uncertainty;
Conference_Titel :
American Control Conference, 2009. ACC '09.
Conference_Location :
St. Louis, MO
Print_ISBN :
978-1-4244-4523-3
Electronic_ISBN :
0743-1619
DOI :
10.1109/ACC.2009.5160656
