Speaker
Brad Schofield
(CERN)
Description
Optimization-based control is a powerful tool for control design, particularly in cases where control objectives lend themselves to being expressed as cost functions and/or constraints. Model Predictive Control (MPC) is a form of optimization-based control which has been widely used in industrial controls for many years. However, it has not yet been widely adopted at CERN, where classical control architectures are still dominant within the domain of technical infrastructure and industrial controls. In this presentation we reflect on recent experience deploying a Model Predictive Controller in an HVAC system. The focus is on architecture, implementation, and integration with the existing industrial controls framework used at CERN.