Perceptive Engineering to present a paper on the use of digital design techniques in the development of model-based predictive process control strategies.
24 April 2018
Model Predictive Control is an Advanced Process Control technique that is widely used in many process industries. It offers the ability to control a process with multiple Critical Quality Attributes (CQAs) and operational constraints. By simultaneously controlling and optimising process unit operation it is possible to automatically respond to process disturbances such as feed material variability and equipment degradation.
Traditionally, Model Predictive Controllers employ data-driven process models. The drawback of this approach is the time and material costs associated with executing the process response tests required for model development and validation. In most cases, the product generated during these tests is discarded. A more efficient approach is to employ digital design techniques to reduce the requirement for process run time during controller development. These techniques include the application of mechanistic models to provide a virtual plant for controller development.
The presentation describes several case-studies where digital design and hybrid models are used in the development or real-time execution of Model Predictive Control systems. These include applications in Crystallisation and Hot Melt Extrusion.
Further information at apact.co.uk/
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Perceptive Engineering Limited
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