Abstract

In order to meet tight product quality specifications for batch/semi-batch processes, it is vital to monitor and control product quality throughout the batch duration. The ideal strategy is to achieve end-product quality specifications through trajectory tracking control during a batch run. However, due to the lack of in situ sensors for continuous monitoring of batch product quality, the measurements are usually implemented by laboratory assays and are inherently intermittent. Therefore, direct trajectory tracking of batch product quality is challenging in such applications. This paper proposes a practical approach to realise trajectory tracking control of batch product quality in those situations where only intermittent measurements are available. The first step of the approach consists in identifying a projection to latent structures (PLS) model to identify a relationship between readily measured process variable trajectories and intermittently measured batch product quality. Then the identified PLS-based prediction model is transformed into recursive formulation by utilising missing data imputation algorithms. Such recursive formulation allows identified PLS-based model to be readily incorporated as a predictor into standard model predictive control (MPC) framework. Case study employing simulated fed-batch fermentation process used to manufacture penicillin was employed to illustrate the principle and the effectiveness of the proposed approach.

DOI

10.1016/j.jprocont.2014.11.009

Publication Date

2015-01-01

Publication Title

Journal of Process Control

Volume

25

Publisher

Elsevier BV

ISSN

0959-1524

Embargo Period

2024-11-22

Keywords

Batch process control, Projection to latent structures, Intermittent measurements, Disturbance rejection, Model predictive control

First Page

115

Last Page

128

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