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LP methods in MPC of large‐scale systems: Application to paper‐machine CD control
Author(s) -
Dave Prashant,
Willing Dennis A.,
Kudva Gautham K.,
Pekny Joseph F.,
Doyle Francis J.
Publication year - 1997
Publication title -
aiche journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.958
H-Index - 167
eISSN - 1547-5905
pISSN - 0001-1541
DOI - 10.1002/aic.690430416
Subject(s) - model predictive control , robustness (evolution) , linear programming , control theory (sociology) , control (management) , computer science , scale (ratio) , mathematical optimization , control engineering , engineering , mathematics , artificial intelligence , chemistry , biochemistry , physics , quantum mechanics , gene
An application of a linear‐programming based model‐predictive control strategy to the paper‐machine cross‐direction (CD) control problem is presented. The objective of CD control is to maintain flat profiles of variables of interest by minimizing worst‐case deviations from setpoints (defects). These control problems can have as many as 200 actuatiors (inputs) and 400 sensor measurements (outputs). This large size coupled with the stringent real‐time requiremnt of computing a control move in a few seconds poses a very challenging control problem. The LP‐based strategy is particularly well suited for solving such classes of control problems. This strategy has demonstrated its ability to solve large‐scale control problems (over 100 inputs and 100 outputs) in real time and exhibits robustness to model uncertainty.