Abstract

This contribution presents a novel process analytical technology (PAT) software interface for online monitoring and control of commercial high-pressure liquid chromatography (HPLC) systems. The developed interface is an add-on to chromatography control software and uses industry-standard bidirectional communication protocols to link sensor technologies with the individual HPLC system components in an overall automation framework that facilitates data acquisition, central operation and control of all instruments. The interface is encoded in the Python™ scripting language and supports versatile data transfer to chromatography control software using either OPC (OLE for process control) or COM (component object model) technologies, which are both based on client/server architectures. By these means, the interface utilizes the flexibility of the high-level programming language for formulating optimal control strategies and enables (semantic) interoperability between the chromatography control software and user defined scripts as well as third-party scientific libraries and numerical packages. The advantages and applicability of the developed interface are highlighted through the implementation of a model-based iterative learning control strategy, in order to assure batch-to-batch repeatability, and open-loop optimal controlled elution trajectories on a commercial HPLC separation system. It is, however, noteworthy that the software interface is completely generic and constitutes a novel framework for implementing any PID control schemes as well as sequential optimal experimental design and model predictive control strategies.

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