Model predictive control—Building a bridge between theory and practice

Abstract

This paper describes the development of an MPC product at AspenTech. A brief historical view sets the stage, describing collaboration with university researchers that formed much of the technical foundation. Gaps between theory and practice were addressed during product development. Major effort focused on eliminating the need for practitioners to understand control theory, while ensuring that controllers satisfy theoretical requirements. This allows control strategies to be designed and implemented via configuration and tuning in a domain familiar to a process operations engineer. Terms like eigenvalue, covariance, detectability, controllability, etc. are never exposed. Robust numerical algorithms and software suitable for real time execution must augment the control theory foundation. Best practices and expertise are embedded in the software realization, thus reducing the skill level required for success while still allowing experts to push the envelope. The resulting technical scalability facilitates a wide range of process control practice in a single framework.