Real-time feasibility of nonlinear model predictive control for semi-batch reactors subject to uncertainty and disturbances

• Published in: Computers & chemical engineering Vol. 133; p. 106529
• Main Authors: Arellano-Garcia, Harvey, Barz, Tilman, Dorneanu, Bogdan, Vassiliadis, Vassilios S.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 02.02.2020
• Subjects: Batch processes; Chance-constraints; Dynamic real time optimisation; NMPC; Output-constraints; Safety; Output-constraints; Dynamic real time optimisation; Safety; Chance-constraints; Batch processes; NMPC
• ISSN: 0098-1354
• DOI: 10.1016/j.compchemeng.2019.106529

This paper presents two nonlinear model predictive control based methods for solving closed-loop stochastic dynamic optimisation problems, ensuring both robustness and feasibility with respect to state output constraints. The first one is a new deterministic approach, using the wait-and-see strategy. The key idea is to specifically anticipate violation of output hard-constraints, which are strongly affected by instantaneous disturbances, by backing off of their bounds along the moving horizon. The second method is a stochastic approach to solve nonlinear chance-constrained dynamic optimisation problems under uncertainties. The key aspect is the explicit consideration of the stochastic properties of both exogenous and endogenous uncertainties in the problem formulation (here-and-now strategy). The approach considers a nonlinear relation between uncertain inputs and the constrained state outputs. The performance of the proposed methodologies is assessed via an application to a semi-batch reactor under safety constraints, involving strongly exothermic reactions.