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

Liu, Y; Yang, X; Xiong, Z; Zhang, J

doi:10.1007/11427469_19

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

Downloads

Full text for this publication is not currently held within this repository. Alternative links are provided below where available.

Abstract

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.