DocumentCode :
592506
Title :
Batch-to-batch strategies for cooling crystallization
Author :
Forgione, Marco ; Mesbah, Ali ; Bombois, Xavier ; Van den Hof, Paul M. J.
Author_Institution :
Delft Center for Syst. & Control, Delft Univ. of Technol., Delft, Netherlands
fYear :
2012
fDate :
10-13 Dec. 2012
Firstpage :
6364
Lastpage :
6369
Abstract :
Two batch-to-batch (B2B) algorithms for supersaturation control in cooling crystallization are presented in this paper. In Iterative Learning Control (ILC) a nominal process model is adjusted with an additive correction term which depends on the error in the last batch. In Iterative Identification Control (IIC) the physical parameters of the process model are recursively estimated by adopting a Bayesian identification framework. Both B2B algorithms compute an optimized input for the next batch that is fed to a lower level PI feedback controller in order to reject the process disturbances. The tracking performance of these B2B+PI control schemes is investigated in a simulation study.
Keywords :
PI control; batch processing (industrial); cooling; crystallisation; feedback; process control; B2B algorithms; B2B+PI control schemes; Bayesian identification framework; PI feedback controller; additive correction term; batch-to-batch algorithms; batch-to-batch strategies; cooling crystallization; iterative learning control; nominal process model; physical parameters; process disturbances; tracking performance; Computational modeling; Crystallization; Equations; Mathematical model; Temperature control; Temperature measurement; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control (CDC), 2012 IEEE 51st Annual Conference on
Conference_Location :
Maui, HI
ISSN :
0743-1546
Print_ISBN :
978-1-4673-2065-8
Electronic_ISBN :
0743-1546
Type :
conf
DOI :
10.1109/CDC.2012.6426773
Filename :
6426773
Link To Document :
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