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Iterative learning control of a crystallisation process using batch wise updated linearised models identified using PLS

Lookup NU author(s): Dr Jie ZhangORCiD, Emeritus Professor Julian Morris


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An iterative learning control strategy with batch wise updated linearised models identified using partial least square (PLS) regression is proposed in this paper. Taking the immediate previous batch as the reference batch, the linearised model relates the deviations in the control profiles with the deviations in the quality variable trajectories between the current and the reference batches. The linearised model is used in calculating the control policy updating for the current batch. The proposed method is applied to a batch crystallisation process and simulation results show that the proposed method can overcome the effect of disturbance and improve the process operation from batch to batch. © 2009 Elsevier B.V. All rights reserved.

Publication metadata

Author(s): Zhang J, Nguyan J, Morris J

Editor(s): Jezowski, J., Thullie, J.

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: Computer Aided Chemical Engineering: 19th European Symposium on Computer Aided Process Engineering

Year of Conference: 2009

Pages: 387-392

ISSN: 1570-7946

Publisher: Springer


DOI: 10.1016/S1570-7946(09)70065-3

Library holdings: Search Newcastle University Library for this item

ISBN: 9780444534330