dc.contributor.author | Suwartadi, Eka | |
dc.contributor.author | Jaschke, Johannes | |
dc.date.accessioned | 2017-10-24T13:44:08Z | |
dc.date.available | 2017-10-24T13:44:08Z | |
dc.date.created | 2017-02-27T15:30:51Z | |
dc.date.issued | 2017 | |
dc.identifier.issn | 2227-9717 | |
dc.identifier.uri | http://hdl.handle.net/11250/2461921 | |
dc.description.abstract | We present a sensitivity-based predictor-corrector path-following algorithm for fast nonlinear model predictive control (NMPC) and demonstrate it on a large case study with an economic cost function. The path-following method is applied within the advanced-step NMPC framework to obtain fast and accurate approximate solutions of the NMPC problem. In our approach, we solve a sequence of quadratic programs to trace the optimal NMPC solution along a parameter change. A distinguishing feature of the path-following algorithm in this paper is that the strongly-active inequality constraints are included as equality constraints in the quadratic programs, while the weakly-active constraints are left as inequalities. This leads to close tracking of the optimal solution. The approach is applied to an economic NMPC case study consisting of a process with a reactor, a distillation column and a recycler. We compare the path-following NMPC solution with an ideal NMPC solution, which is obtained by solving the full nonlinear programming problem. Our simulations show that the proposed algorithm effectively traces the exact solution. | nb_NO |
dc.language.iso | eng | nb_NO |
dc.publisher | MDPI | nb_NO |
dc.rights | Navngivelse 4.0 Internasjonal | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/deed.no | * |
dc.title | Sensitivity-Based Economic NMPC with a Path-Following Approach | nb_NO |
dc.type | Journal article | nb_NO |
dc.type | Peer reviewed | nb_NO |
dc.description.version | publishedVersion | nb_NO |
dc.source.journal | Processes | nb_NO |
dc.identifier.doi | 10.3390/pr5010008 | |
dc.identifier.cristin | 1454347 | |
dc.description.localcode | (c) 2017 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/). | nb_NO |
cristin.unitcode | 194,66,30,0 | |
cristin.unitname | Institutt for kjemisk prosessteknologi | |
cristin.ispublished | true | |
cristin.fulltext | original | |
cristin.qualitycode | 1 | |