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Advanced Control Techniques for Batch Processes Based on Iterative Learning Control Methods  

Lee, Kwang Soon (Depart. of Chem. and Biomol. Engng., Sogang Univ.)
Publication Information
Korean Chemical Engineering Research / v.44, no.5, 2006 , pp. 425-434 More about this Journal
Abstract
The operability and productivity of continuous processes, especially in petrochemical industries have made remarkable improvement during the past twenty years through advanced process control (APC) typified by model-based predictive control. On the other hand, APC have not been actively practiced in industrial batch processes typified by batch polymerization reactors. Perhaps the main cause for this has been the lack of reliable batch process APC techniques that can overcome the unique problems in industrial batch processes. Recently, some noteworthy progress is being made in this area. New high-performance batch process control techniques that can accommodate and also overcome the unique problems of industrial batch processes have been proposed on the basis of iterative learning control (ILC). In this review paper, recent advancement in the batch process APC techniques are presented, with a particular focus on the variations of the so called Q-ILC method, with the hope that they are widely practiced in different industrial batch processes and enhance their operations.
Keywords
Batch Process; Advanced Process Control; Iterative Learning Control;
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