Author/Authors :
K.S. Lee and J.H. Lee، نويسنده ,
Title Of Article :
Iterative learning control-based batch
process controlt echnique for
integrated controlof end product
properties and transient profiles of
process variables
Latin Abstract :
Importance of batch processes has grown recently with the increasing economic competition that has pushed the manufacturing
industries to pursue small quantity production of diverse high value-added products. Accordingly, systems engineering research on
advanced control and optimization of batch processes has proliferated. In this paper, we examine the potentials of ‘iterative learning
control (ILC)’ as a framework for industrial batch process control and optimization. First, various ILC rules are reviewed to
provide a historical perspective. Next it is shown how the concept of ILC can be fused with model predictive control (MPC) to build
an integrated end product and transient profile control technique for industrial chemical batch processes. Possible extensions and
modifications of the technique are also presented along with some numerical illustrations. Finally, other related techniques are
introduced to note the similarities and contemplate the opportunities for synergistic integration with the current ILC framework.
NaturalLanguageKeyword :
Model predictive control , Iterative learning control , Batch process control
JournalTitle :
Studia Iranica
