(577a) Recent Advances in Multi-Parametric Optimization & Explicit Model Predictive Control

Optimization under uncertainty is an area in which Professor Ignacio Grossmann has made pivotal transformational contributions throughout his career. In celebration of his impact on the process systems engineering field on the occasion of his 75th birthday, here we report on recent advances in the area of optimization under uncertainty, with main focus on multi-parametric optimization and explicit model predictive control. In particular, we discuss (i) the key features of a general-purpose python-based multiparametric optimization toolbox [PPOPT]; (ii) theoretical developments to explicitly incorporate probabilistic-based constraints within multiparametric optimization; and (iii) new directions for explicit nonlinear time-varying model predictive control via exploring the properties of the underlying approximate multiparametric linear ODE systems.