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Iterative Learning Control of a Crystallisation Process Using Batch Wise Updated Linearised Models

Lookup NU author(s): Dr Jie ZhangORCiD


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An iterative learning control strategy with batch wise updated linearised models identified using principal component regression (PCR) is proposed in this paper for the supersaturation control of a batch crystallization process. 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. Simulation results show that the proposed method can overcome the effect of disturbance and improve the process operation from batch to batch.

Publication metadata

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

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: 21st Chinese Control and Decision Conference (CCDC)

Year of Conference: 2009

Number of Volumes: 6

Pages: 1734-1739

Publisher: IEEE


DOI: 10.1109/CCDC.2009.5192272

Library holdings: Search Newcastle University Library for this item

ISBN: 9781424427222