Charitopoulos, VM;
Papageorgiou, LG;
Dua, V;
(2021)
Multi set-point explicit model predictive control for nonlinear process systems.
Processes
, 9
(7)
, Article 1156. 10.3390/pr9071156.
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Abstract
In this article, we introduce a novel framework for the design of multi set-point nonlinear explicit controllers for process systems engineering problems where the set-points are treated as uncertain parameters simultaneously with the initial state of the dynamical system at each sampling instance. To this end, an algorithm for a special class of multi-parametric nonlinear programming problems with uncertain parameters on the right-hand side of the constraints and the cost coefficients of the objective function is presented. The algorithm is based on computed algebra methods for symbolic manipulation that enable an analytical solution of the optimality conditions of the underlying multi-parametric nonlinear program. A notable property of the presented algorithm is the computation of exact, in general nonconvex, critical regions that results in potentially great computational savings through a reduction in the number of convex approximate critical regions.
| Type: | Article |
|---|---|
| Title: | Multi set-point explicit model predictive control for nonlinear process systems |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.3390/pr9071156 |
| Publisher version: | https://doi.org/10.3390/pr9071156 |
| Language: | English |
| Additional information: | This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited |
| Keywords: | multi-parametric programming; explicit MPC; enterprise-wide optimisation; set-point tracking; algebraic geometry |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Chemical Engineering |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10131152 |
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