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Batch-to-batch optimal control based on support vector regression model

Lookup NU author(s): Dr Jie ZhangORCiD


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A support vector regression (SVR) model based batch to batch optimal control strategy is proposed in this paper. Because of model plant mismatches and unknown disturbances the control performance of optimal control profile calculated from empirical model is deteriorated. Due to the repetitive nature of batch processes, it is possible to improve the operation of the next batch using the information of the current and previous batch runs. A batch to batch optimal control strategy based on the linearization of the SVR model around the control profile is proposed in this paper. Applications to a simulated batch styrene polymerization reactor demonstrate that the proposed method can improve process performance from batch to batch in the presence of model plant mismatches and unknown disturbances. © Springer-Verlag Berlin Heidelberg 2005.

Publication metadata

Author(s): Liu Y, Yang X, Xiong Z, Zhang J

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: Advances in Neural Networks – ISNN 2005. Second International Symposium on Neural Networks

Year of Conference: 2005

Pages: 125-130

ISSN: 0302-9743

Publisher: Springer


DOI: 10.1007/11427469_19

Notes: Book doi: 10.1007/b136479

Library holdings: Search Newcastle University Library for this item

Series Title: Lecture Notes in Computer Science

ISBN: 9783540259145