Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-642-15621-2_14
Title: Batch-to-batch iterative optimal control of batch processes based on dynamic quadratic criterion
Authors: Jia, L.
Shi, J.
Cheng, D.
Cao, L.
Chiu, M.-S. 
Keywords: batch processes
iterative learning control
quadratic criterion
Issue Date: 2010
Source: Jia, L., Shi, J., Cheng, D., Cao, L., Chiu, M.-S. (2010). Batch-to-batch iterative optimal control of batch processes based on dynamic quadratic criterion. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 6328 LNCS (PART 1) : 112-119. ScholarBank@NUS Repository. https://doi.org/10.1007/978-3-642-15621-2_14
Abstract: A novel dynamic parameters-based quadratic criterion-iterative learning control is proposed in this paper. Firstly, quadratic criterion-iterative learning control with dynamic parameters is used to improve the performance of iterative learning control. As a result, the proposed method can avoid the problem of initialization of the optimization controller parameters, which are usually resorted to trial and error procedure in the existing iterative algorithms used for the optimization of batch process. Next, we make the first attempt to give rigorous description and proof to verify that a perfect tracking performance can be obtained. Lastly, examples are used to illustrate the performance and applicability of the proposed method. © 2010 Springer-Verlag.
Source Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
URI: http://scholarbank.nus.edu.sg/handle/10635/74492
ISBN: 3642156207
ISSN: 03029743
DOI: 10.1007/978-3-642-15621-2_14
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