Gast ::
| Hauptseite > Publikationsdatenbank > Nonlinear model predictive control of ultra-high-purity air separation units using transient wave propagation model > print |
| Hauptseite > Publikationsdatenbank > Nonlinear model predictive control of ultra-high-purity air separation units using transient wave propagation model > print |
| 001 | 888872 | ||
| 005 | 20240712112853.0 | ||
| 024 | 7 | _ | |a 10.1016/j.compchemeng.2020.107163 |2 doi |
| 024 | 7 | _ | |a 0098-1354 |2 ISSN |
| 024 | 7 | _ | |a 1873-4375 |2 ISSN |
| 024 | 7 | _ | |a 2128/26772 |2 Handle |
| 024 | 7 | _ | |a WOS:000608130700019 |2 WOS |
| 037 | _ | _ | |a FZJ-2020-05282 |
| 082 | _ | _ | |a 660 |
| 100 | 1 | _ | |a Schulze, Jan C. |0 P:(DE-HGF)0 |b 0 |
| 245 | _ | _ | |a Nonlinear model predictive control of ultra-high-purity air separation units using transient wave propagation model |
| 260 | _ | _ | |a Amsterdam [u.a.] |c 2021 |b Elsevier Science |
| 336 | 7 | _ | |a article |2 DRIVER |
| 336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
| 336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1639555050_11080 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a ARTICLE |2 BibTeX |
| 336 | 7 | _ | |a JOURNAL_ARTICLE |2 ORCID |
| 336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
| 520 | _ | _ | |a Model reduction techniques can be used to reduce the computational burden associated with nonlinear model predictive control (NMPC). In our recent work, we introduced the transient nonlinear wave propagation model (TWPM) for reduced dynamic modeling of multi-component distillation columns with variable holdup, and demonstrated its suitability for optimization and control of single-section distillation columns and simple air separation units [Caspari et al., J. Process Control, 2020]. We show here that the TWPM is well-suited for reduced modeling of multi-sectional ultra-high-purity distillation columns and enables real-time capable NMPC of complex process flowsheets with tight operational constraints. To demonstrate its performance and accuracy, we apply the TWPM for NMPC of an ultra-high-purity nitrogen air separation unit. We perform an in-silico closed-loop case study comprising a series of load changes. Our approach reduces CPU time by 84%, enabling NMPC in real time. |
| 536 | _ | _ | |a 1122 - Design, Operation and Digitalization of the Future Energy Grids (POF4-112) |0 G:(DE-HGF)POF4-1122 |c POF4-112 |f POF IV |x 0 |
| 588 | _ | _ | |a Dataset connected to CrossRef |
| 700 | 1 | _ | |a Caspari, Adrian |0 P:(DE-HGF)0 |b 1 |
| 700 | 1 | _ | |a Offermanns, Christoph |0 P:(DE-HGF)0 |b 2 |
| 700 | 1 | _ | |a Mhamdi, Adel |0 P:(DE-HGF)0 |b 3 |
| 700 | 1 | _ | |a Mitsos, Alexander |0 P:(DE-Juel1)172025 |b 4 |e Corresponding author |u fzj |
| 773 | _ | _ | |a 10.1016/j.compchemeng.2020.107163 |g p. 107163 - |0 PERI:(DE-600)1499971-7 |p 107163 |t Computers & chemical engineering |v 145 |y 2021 |x 0098-1354 |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/888872/files/Schulze%202020%20-%20Nonlinear%20Model%20Predictive%20Control%20of%20Ultra-High-Purity%20Air%20Separation%20Units.pdf |y OpenAccess |
| 909 | C | O | |o oai:juser.fz-juelich.de:888872 |p openaire |p open_access |p VDB |p driver |p dnbdelivery |
| 910 | 1 | _ | |a RWTH Aachen |0 I:(DE-588b)36225-6 |k RWTH |b 0 |6 P:(DE-HGF)0 |
| 910 | 1 | _ | |a RWTH Aachen |0 I:(DE-588b)36225-6 |k RWTH |b 1 |6 P:(DE-HGF)0 |
| 910 | 1 | _ | |a RWTH Aachen |0 I:(DE-588b)36225-6 |k RWTH |b 2 |6 P:(DE-HGF)0 |
| 910 | 1 | _ | |a RWTH Aachen |0 I:(DE-588b)36225-6 |k RWTH |b 3 |6 P:(DE-HGF)0 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 4 |6 P:(DE-Juel1)172025 |
| 910 | 1 | _ | |a RWTH Aachen |0 I:(DE-588b)36225-6 |k RWTH |b 4 |6 P:(DE-Juel1)172025 |
| 913 | 1 | _ | |a DE-HGF |b Forschungsbereich Energie |l Energiesystemdesign (ESD) |1 G:(DE-HGF)POF4-110 |0 G:(DE-HGF)POF4-112 |3 G:(DE-HGF)POF4 |2 G:(DE-HGF)POF4-100 |4 G:(DE-HGF)POF |v Digitalisierung und Systemtechnik |9 G:(DE-HGF)POF4-1122 |x 0 |
| 914 | 1 | _ | |y 2021 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0200 |2 StatID |b SCOPUS |d 2020-09-09 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0160 |2 StatID |b Essential Science Indicators |d 2020-09-09 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1160 |2 StatID |b Current Contents - Engineering, Computing and Technology |d 2020-09-09 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0600 |2 StatID |b Ebsco Academic Search |d 2020-09-09 |
| 915 | _ | _ | |a JCR |0 StatID:(DE-HGF)0100 |2 StatID |b COMPUT CHEM ENG : 2018 |d 2020-09-09 |
| 915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0113 |2 StatID |b Science Citation Index Expanded |d 2020-09-09 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0150 |2 StatID |b Web of Science Core Collection |d 2020-09-09 |
| 915 | _ | _ | |a IF < 5 |0 StatID:(DE-HGF)9900 |2 StatID |d 2020-09-09 |
| 915 | _ | _ | |a OpenAccess |0 StatID:(DE-HGF)0510 |2 StatID |
| 915 | _ | _ | |a Peer Review |0 StatID:(DE-HGF)0030 |2 StatID |b ASC |d 2020-09-09 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0300 |2 StatID |b Medline |d 2020-09-09 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0199 |2 StatID |b Clarivate Analytics Master Journal List |d 2020-09-09 |
| 920 | _ | _ | |l yes |
| 920 | 1 | _ | |0 I:(DE-Juel1)IEK-10-20170217 |k IEK-10 |l Modellierung von Energiesystemen |x 0 |
| 980 | 1 | _ | |a FullTexts |
| 980 | _ | _ | |a journal |
| 980 | _ | _ | |a VDB |
| 980 | _ | _ | |a I:(DE-Juel1)IEK-10-20170217 |
| 980 | _ | _ | |a UNRESTRICTED |
| 981 | _ | _ | |a I:(DE-Juel1)ICE-1-20170217 |
| Library | Collection | CLSMajor | CLSMinor | Language | Author |
|---|