A roadmap for in silico development and evaluation of industrial NMPC applications: A practical case study. (July 2021) - Morandi, Santiago; Nimmegeers, Philippe; Schwind, Markus; Di Pretoro, Alessandro; Manenti, Flavio; Logist, Filip
Highlights: Roadmap for implementing nonlinear model predictive controllers (NMPC) is elaborated. Steps are potential evaluation, process modeling, controller simulations and fallback strategies development. Demo case is presented for an industrial exothermal semi-batch process. NMPC showed improved performance compared to PID control. Abstract: Linear Model Predictive Control (MPC) can be considered as the state of the art advanced process control technology in model-based automation of continuous chemical processes. For (semi-)batch processes, that often present a strongly nonlinear (or even unstable) behavior in combination with fast dynamics, Nonlinear Model Predictive Control (NMPC) is a more suited technology. However, online applications of NMPC have a hard time to penetrate in industry despite methodological developments, tools and examples in academia. In this paper, we propose a roadmap to argue against the intrinsic reasons and practical limitations that slow down the practical online applications of NMPC. This roadmap is applied to an existing semi-batch plant as a practical case study. The results have shown that the NMPC algorithm can provide an improved control, namely a better tracking of the main process variables, a reduction in the reaction time, and robustness with respect to model-plant mismatch and disturbances.