Please use this identifier to cite or link to this item: https://doi.org/10.1007/s11741-009-0401-1
Title: Run-to-run product quality control of batch processes
Authors: Jia, L.
Shi, J.-P.
Cheng, D.-S.
Chiu, M.-S. 
Keywords: Batch processes
Iterative learning optimization control
Tracking error
Issue Date: Aug-2009
Source: Jia, L.,Shi, J.-P.,Cheng, D.-S.,Chiu, M.-S. (2009-08). Run-to-run product quality control of batch processes. Journal of Shanghai University 13 (4) : 267-269. ScholarBank@NUS Repository. https://doi.org/10.1007/s11741-009-0401-1
Abstract: Batch processes have been increasingly used in the production of low volume and high value added products. Consequently, optimization control in batch processes is crucial in order to derive the maximum benefit. In this paper, a run-to-run product quality control based on iterative learning optimization control is developed. Moreover, a rigorous theorem is proposed and proven in this paper, which states that the tracking error under the optimal iterative learning control (ILC) law can converge to zero. In this paper, a typical nonlinear batch continuous stirred tank reactor (CSTR) is considered, and the results show that the performance of trajectory tracking is gradually improved by the ILC. © 2009 Shanghai University and Springer-Verlag GmbH.
Source Title: Journal of Shanghai University
URI: http://scholarbank.nus.edu.sg/handle/10635/64539
ISSN: 10076417
DOI: 10.1007/s11741-009-0401-1
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