Article
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Preserved in Portico This version is not peer-reviewed
Application of Intelligent Control in Chromatography Separation Process
Version 1
: Received: 7 November 2023 / Approved: 7 November 2023 / Online: 7 November 2023 (10:40:02 CET)
A peer-reviewed article of this Preprint also exists.
Xie, C.-F.; Zhang, H.; Hwang, R.-C. Application of Intelligent Control in Chromatography Separation Process. Processes 2023, 11, 3443. Xie, C.-F.; Zhang, H.; Hwang, R.-C. Application of Intelligent Control in Chromatography Separation Process. Processes 2023, 11, 3443.
Abstract
Chromatographic separation is a critical technique in the manufacturing processes of both chemical products and biopharmaceuticals. Its principle relies on exploiting the differences in distribution between the stationary and mobile phases to achieve the separation of mixtures. The precision of substance concentration during separation directly impacts the quality and usability of the final product. Therefore, the development of an effective and precise separation control technique has long been a vital concern in the field of chromatographic separation control. Currently, the employment of Simulated Moving Bed (SMB) technology for chromatographic separation, which allows for continuous feed, has been recognized as a cutting-edge technique. SMB is a continuous process technology that enhances the efficiency of adsorbents within the bed. This sequential multi-column SMB technology not only increases production capacity but also reduces the consumption of solvents and water. It is acknowledged as one of the cleanest manufacturing technologies in the biopharmaceutical industry. However, multi-column SMB involves various variables such as flow rates in multiple sections and valve switching times, rendering its system control highly complex. Unlike traditional control objectives that aim to minimize control output errors, the control objective of SMB is to achieve a specific proportion of substance concentration. Consequently, designing and implementing traditional control theories for SMB is challenging, leading to SMB systems largely being controlled based on simple PLC controls. Moreover, these controls are often applicable only to single or a few-column SMB setups, limiting the effectiveness of high-capacity applications. To achieve effective control of SMB, this study employs an adjustable intelligent fuzzy controller with a structure like an approximate neural network (NN) for SMB control research. Simulation results demonstrate that the intelligent controller effectively achieves desirable control outcomes for the SMB system.
Keywords
Chromatographic separation; SMB; multi-column; fuzzy; neural network
Subject
Engineering, Chemical Engineering
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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