Explicit model predictive control through robust optimizationExplicit model predictive control through robust optimization Peer-Reviewed Journal Publication Δημοσίευση σε Περιοδικό με Κριτές 2025-07-292023enA strategy that calculates an explicit state feedback policy to regulate constrained uncertain discrete-time uncertain linear systems is presented. We consider uncertain processes, affected by box-bounded multiplicative uncertainty as well as bounded additive uncertainty with linear state and inputs constraints. The proposed method includes (i) the calculation of a terminal set constraint and (ii) the robust reformulation of state constraints in the prediction horizon. These features allow the derivation of the desired policy by solving a single multiparametric quadratic programming problem that guarantees feasible operation in the presence of uncertainty. Additionally, we employ variable and constraint elimination approaches to enhance the computational performance of the strategy. We demonstrate the steps and benefits of these developments with a numerical example and a chemical engineering case study.http://creativecommons.org/licenses/by-nc-nd/4.0/AIChE Journal6910Pappas_et_al_AIChE J._69(10)_2023.pdfChania [Greece]Library of TUC2025-07-29application/pdf1.5 MBfree Pappas Iosif Diangelakis Nikolaos Διαγγελακης Νικολαος Pistikopoulos Stratos Wiley Explicit model predictive control Multiparametric programming Optimization under uncertainty Robust optimization