Rapid development of modular and sustainable nonlinear model predictive control solutions

While computational complexity is often not anymore an obstacle for the application of Nonlinear Model Predictive Control (NMPC), there are still important challenges that prevent NMPC from already being an industrial reality. This paper deals with a critical challenge: the lack of tools that facilitate the sustainable development of robust NMPC solutions. This paper proposes a modularization of the NMPC implementations that facilitates the comparison of different solutions and the transition from simulation to online application. The proposed platform supports the multi-stage robust NMPC approach to deal with uncertainty. Its benefits are demonstrated by experimental results for a laboratory plant.