Real-time feasibility of nonlinear model predictive control for semi-batch reactors subject to uncertainty and disturbances
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Publication Date
2020-02-02Journal Title
Computers and Chemical Engineering
ISSN
0098-1354
Publisher
Elsevier Ltd.
Volume
133
Type
Article
This Version
AM
Metadata
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Arellano-Garcia, H., Barz, T., Dorneanu, B., & Vassiliadis, V. (2020). Real-time feasibility of nonlinear model predictive control for semi-batch reactors subject to uncertainty and disturbances. Computers and Chemical Engineering, 133 https://doi.org/10.1016/j.compchemeng.2019.106529
Abstract
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.
Embargo Lift Date
2021-02-02
Identifiers
External DOI: https://doi.org/10.1016/j.compchemeng.2019.106529
This record's URL: https://www.repository.cam.ac.uk/handle/1810/295800
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International
Licence URL: https://creativecommons.org/licenses/by-nc-nd/4.0/