Advanced control of a continuous oscillatory flow crystalliser

F. Tahir; K. Krzemieniewska-Nandwani; J. Mack; D. Lovett; H. Siddique; F. Mabbott; V. Raval; I. Houson; A. Florence

doi:10.1016/j.conengprac.2017.07.008

Advanced control of a continuous oscillatory flow crystalliser

F. Tahir^*, K. Krzemieniewska-Nandwani, J. Mack, D. Lovett, H. Siddique, F. Mabbott, V. Raval, I. Houson, A. Florence

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

15 Citations (Scopus)

Abstract

This paper presents the application and challenges of achieving Model Predictive Control (MPC) on two continuous oscillatory baffled crystallisation reactors, delivering precise product quality control in the face of raw material fluctuations. A key advantage of MPC is that it effectively deals with multivariable interactions and constraints that appear within the continuous crystallisation process. Using a flexible real-time software package, a control scheme is proposed that incorporates three MPC blocks for controlling reactor cooling profile, API (Active Pharmaceutical Ingredient) concentration and crystal size distribution, respectively. Furthermore, the solution is customisable and transferable to different crystallisation reactors as well as various APIs.

Original language	English
Pages (from-to)	64-75
Number of pages	12
Journal	Control Engineering Practice
Volume	67
Early online date	10 Aug 2017
DOIs	https://doi.org/10.1016/j.conengprac.2017.07.008
Publication status	Published - 1 Oct 2017

Keywords

calibration models
continuous crystallisation
crystal PSD
model predictive control
super-saturation control

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10.1016/j.conengprac.2017.07.008

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abstract = "This paper presents the application and challenges of achieving Model Predictive Control (MPC) on two continuous oscillatory baffled crystallisation reactors, delivering precise product quality control in the face of raw material fluctuations. A key advantage of MPC is that it effectively deals with multivariable interactions and constraints that appear within the continuous crystallisation process. Using a flexible real-time software package, a control scheme is proposed that incorporates three MPC blocks for controlling reactor cooling profile, API (Active Pharmaceutical Ingredient) concentration and crystal size distribution, respectively. Furthermore, the solution is customisable and transferable to different crystallisation reactors as well as various APIs.",

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AU - Tahir, F.

AU - Krzemieniewska-Nandwani, K.

AU - Mack, J.

AU - Lovett, D.

AU - Siddique, H.

AU - Mabbott, F.

AU - Raval, V.

AU - Houson, I.

AU - Florence, A.

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N2 - This paper presents the application and challenges of achieving Model Predictive Control (MPC) on two continuous oscillatory baffled crystallisation reactors, delivering precise product quality control in the face of raw material fluctuations. A key advantage of MPC is that it effectively deals with multivariable interactions and constraints that appear within the continuous crystallisation process. Using a flexible real-time software package, a control scheme is proposed that incorporates three MPC blocks for controlling reactor cooling profile, API (Active Pharmaceutical Ingredient) concentration and crystal size distribution, respectively. Furthermore, the solution is customisable and transferable to different crystallisation reactors as well as various APIs.

AB - This paper presents the application and challenges of achieving Model Predictive Control (MPC) on two continuous oscillatory baffled crystallisation reactors, delivering precise product quality control in the face of raw material fluctuations. A key advantage of MPC is that it effectively deals with multivariable interactions and constraints that appear within the continuous crystallisation process. Using a flexible real-time software package, a control scheme is proposed that incorporates three MPC blocks for controlling reactor cooling profile, API (Active Pharmaceutical Ingredient) concentration and crystal size distribution, respectively. Furthermore, the solution is customisable and transferable to different crystallisation reactors as well as various APIs.

KW - calibration models

KW - continuous crystallisation

KW - crystal PSD

KW - model predictive control

KW - super-saturation control

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JO - Control Engineering Practice

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Advanced control of a continuous oscillatory flow crystalliser

Abstract

Keywords

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