---
_id: '16219'
abstract:
- lang: eng
text: "Network function virtualization (NFV) proposes\r\nto replace physical middleboxes
with more flexible virtual\r\nnetwork functions (VNFs). To dynamically adjust
to everchanging\r\ntraffic demands, VNFs have to be instantiated and\r\ntheir
allocated resources have to be adjusted on demand.\r\nDeciding the amount of allocated
resources is non-trivial.\r\nExisting optimization approaches often assume fixed
resource\r\nrequirements for each VNF instance. However, this can easily\r\nlead
to either waste of resources or bad service quality if too\r\nmany or too few
resources are allocated.\r\n\r\nTo solve this problem, we train machine learning
models\r\non real VNF data, containing measurements of performance\r\nand resource
requirements. For each VNF, the trained models\r\ncan then accurately predict
the required resources to handle\r\na certain traffic load. We integrate these
machine learning\r\nmodels into an algorithm for joint VNF scaling and placement\r\nand
evaluate their impact on resulting VNF placements. Our\r\nevaluation based on
real-world data shows that using suitable\r\nmachine learning models effectively
avoids over- and underallocation\r\nof resources, leading to up to 12 times lower
resource\r\nconsumption and better service quality with up to 4.5 times\r\nlower
total delay than using standard fixed resource allocation."
author:
- first_name: Stefan Balthasar
full_name: Schneider, Stefan Balthasar
id: '35343'
last_name: Schneider
orcid: 0000-0001-8210-4011
- first_name: Narayanan Puthenpurayil
full_name: Satheeschandran, Narayanan Puthenpurayil
last_name: Satheeschandran
- first_name: Manuel
full_name: Peuster, Manuel
id: '13271'
last_name: Peuster
- first_name: Holger
full_name: Karl, Holger
id: '126'
last_name: Karl
citation:
ama: 'Schneider SB, Satheeschandran NP, Peuster M, Karl H. Machine Learning for
Dynamic Resource Allocation in Network Function Virtualization. In: IEEE Conference
on Network Softwarization (NetSoft). IEEE; 2020.'
apa: 'Schneider, S. B., Satheeschandran, N. P., Peuster, M., & Karl, H. (2020).
Machine Learning for Dynamic Resource Allocation in Network Function Virtualization.
In IEEE Conference on Network Softwarization (NetSoft). Ghent, Belgium:
IEEE.'
bibtex: '@inproceedings{Schneider_Satheeschandran_Peuster_Karl_2020, title={Machine
Learning for Dynamic Resource Allocation in Network Function Virtualization},
booktitle={IEEE Conference on Network Softwarization (NetSoft)}, publisher={IEEE},
author={Schneider, Stefan Balthasar and Satheeschandran, Narayanan Puthenpurayil
and Peuster, Manuel and Karl, Holger}, year={2020} }'
chicago: Schneider, Stefan Balthasar, Narayanan Puthenpurayil Satheeschandran, Manuel
Peuster, and Holger Karl. “Machine Learning for Dynamic Resource Allocation in
Network Function Virtualization.” In IEEE Conference on Network Softwarization
(NetSoft). IEEE, 2020.
ieee: S. B. Schneider, N. P. Satheeschandran, M. Peuster, and H. Karl, “Machine
Learning for Dynamic Resource Allocation in Network Function Virtualization,”
in IEEE Conference on Network Softwarization (NetSoft), Ghent, Belgium,
2020.
mla: Schneider, Stefan Balthasar, et al. “Machine Learning for Dynamic Resource
Allocation in Network Function Virtualization.” IEEE Conference on Network
Softwarization (NetSoft), IEEE, 2020.
short: 'S.B. Schneider, N.P. Satheeschandran, M. Peuster, H. Karl, in: IEEE Conference
on Network Softwarization (NetSoft), IEEE, 2020.'
conference:
location: Ghent, Belgium
name: IEEE Conference on Network Softwarization (NetSoft)
date_created: 2020-03-03T11:42:22Z
date_updated: 2022-01-06T06:52:46Z
ddc:
- '000'
department:
- _id: '75'
file:
- access_level: open_access
content_type: application/pdf
creator: stschn
date_created: 2020-03-03T11:42:16Z
date_updated: 2020-03-03T11:42:16Z
file_id: '16220'
file_name: ris_preprint.pdf
file_size: 476590
relation: main_file
file_date_updated: 2020-03-03T11:42:16Z
has_accepted_license: '1'
language:
- iso: eng
oa: '1'
project:
- _id: '28'
grant_number: '761493'
name: 5G Development and validation platform for global industry-specific network
services and Apps
- _id: '1'
name: SFB 901
- _id: '4'
name: SFB 901 - Project Area C
- _id: '16'
name: SFB 901 - Subproject C4
publication: IEEE Conference on Network Softwarization (NetSoft)
publisher: IEEE
status: public
title: Machine Learning for Dynamic Resource Allocation in Network Function Virtualization
type: conference
user_id: '35343'
year: '2020'
...
---
_id: '16222'
author:
- first_name: A.
full_name: Zafeiropoulos, A.
last_name: Zafeiropoulos
- first_name: E.
full_name: Fotopoulou, E.
last_name: Fotopoulou
- first_name: Manuel
full_name: Peuster, Manuel
id: '13271'
last_name: Peuster
- first_name: Stefan Balthasar
full_name: Schneider, Stefan Balthasar
id: '35343'
last_name: Schneider
orcid: 0000-0001-8210-4011
- first_name: P.
full_name: Gouvas, P.
last_name: Gouvas
- first_name: D.
full_name: Behnke, D.
last_name: Behnke
- first_name: M.
full_name: Müller, M.
last_name: Müller
- first_name: P.
full_name: Bök, P.
last_name: Bök
- first_name: P.
full_name: Trakadas, P.
last_name: Trakadas
- first_name: P.
full_name: Karkazis, P.
last_name: Karkazis
- first_name: Holger
full_name: Karl, Holger
id: '126'
last_name: Karl
citation:
ama: 'Zafeiropoulos A, Fotopoulou E, Peuster M, et al. Benchmarking and Profiling
5G Verticals’ Applications: An Industrial IoT Use Case. In: IEEE Conference
on Network Softwarization (NetSoft). ; 2020.'
apa: 'Zafeiropoulos, A., Fotopoulou, E., Peuster, M., Schneider, S. B., Gouvas,
P., Behnke, D., … Karl, H. (2020). Benchmarking and Profiling 5G Verticals’ Applications:
An Industrial IoT Use Case. In IEEE Conference on Network Softwarization (NetSoft).'
bibtex: '@inproceedings{Zafeiropoulos_Fotopoulou_Peuster_Schneider_Gouvas_Behnke_Müller_Bök_Trakadas_Karkazis_et
al._2020, title={Benchmarking and Profiling 5G Verticals’ Applications: An Industrial
IoT Use Case}, booktitle={IEEE Conference on Network Softwarization (NetSoft)},
author={Zafeiropoulos, A. and Fotopoulou, E. and Peuster, Manuel and Schneider,
Stefan Balthasar and Gouvas, P. and Behnke, D. and Müller, M. and Bök, P. and
Trakadas, P. and Karkazis, P. and et al.}, year={2020} }'
chicago: 'Zafeiropoulos, A., E. Fotopoulou, Manuel Peuster, Stefan Balthasar Schneider,
P. Gouvas, D. Behnke, M. Müller, et al. “Benchmarking and Profiling 5G Verticals’
Applications: An Industrial IoT Use Case.” In IEEE Conference on Network Softwarization
(NetSoft), 2020.'
ieee: 'A. Zafeiropoulos et al., “Benchmarking and Profiling 5G Verticals’
Applications: An Industrial IoT Use Case,” in IEEE Conference on Network Softwarization
(NetSoft), 2020.'
mla: 'Zafeiropoulos, A., et al. “Benchmarking and Profiling 5G Verticals’ Applications:
An Industrial IoT Use Case.” IEEE Conference on Network Softwarization (NetSoft),
2020.'
short: 'A. Zafeiropoulos, E. Fotopoulou, M. Peuster, S.B. Schneider, P. Gouvas,
D. Behnke, M. Müller, P. Bök, P. Trakadas, P. Karkazis, H. Karl, in: IEEE Conference
on Network Softwarization (NetSoft), 2020.'
date_created: 2020-03-03T11:51:22Z
date_updated: 2022-01-06T06:52:46Z
department:
- _id: '75'
language:
- iso: eng
project:
- _id: '28'
grant_number: '761493'
name: 5G Development and validation platform for global industry-specific network
services and Apps
publication: IEEE Conference on Network Softwarization (NetSoft)
status: public
title: 'Benchmarking and Profiling 5G Verticals'' Applications: An Industrial IoT
Use Case'
type: conference
user_id: '35343'
year: '2020'
...
---
_id: '16274'
author:
- first_name: Ivan
full_name: Jovanovikj, Ivan
id: '39187'
last_name: Jovanovikj
orcid: https://orcid.org/0000-0002-1838-794X
- first_name: Achyuth
full_name: Nagaraj, Achyuth
last_name: Nagaraj
- first_name: Enes
full_name: Yigitbas, Enes
id: '8447'
last_name: Yigitbas
orcid: 0000-0002-5967-833X
- first_name: Anthony
full_name: Anjorin, Anthony
last_name: Anjorin
- first_name: Stefan
full_name: Sauer, Stefan
id: '447'
last_name: Sauer
- first_name: Gregor
full_name: Engels, Gregor
id: '107'
last_name: Engels
citation:
ama: 'Jovanovikj I, Nagaraj A, Yigitbas E, Anjorin A, Sauer S, Engels G. Validating
Test Case Migration via Mutation Analysis . In: Proceedings of the 1st IEEE/ACM
International Conference on Automation of Software Test AST. ACM; 2020:31-40.'
apa: 'Jovanovikj, I., Nagaraj, A., Yigitbas, E., Anjorin, A., Sauer, S., & Engels,
G. (2020). Validating Test Case Migration via Mutation Analysis . In Proceedings
of the 1st IEEE/ACM International Conference on Automation of Software Test AST
(pp. 31–40). Seoul: ACM.'
bibtex: '@inproceedings{Jovanovikj_Nagaraj_Yigitbas_Anjorin_Sauer_Engels_2020, title={Validating
Test Case Migration via Mutation Analysis }, booktitle={Proceedings of the 1st
IEEE/ACM International Conference on Automation of Software Test AST}, publisher={ACM},
author={Jovanovikj, Ivan and Nagaraj, Achyuth and Yigitbas, Enes and Anjorin,
Anthony and Sauer, Stefan and Engels, Gregor}, year={2020}, pages={31–40} }'
chicago: Jovanovikj, Ivan, Achyuth Nagaraj, Enes Yigitbas, Anthony Anjorin, Stefan
Sauer, and Gregor Engels. “Validating Test Case Migration via Mutation Analysis
.” In Proceedings of the 1st IEEE/ACM International Conference on Automation
of Software Test AST, 31–40. ACM, 2020.
ieee: I. Jovanovikj, A. Nagaraj, E. Yigitbas, A. Anjorin, S. Sauer, and G. Engels,
“Validating Test Case Migration via Mutation Analysis ,” in Proceedings of
the 1st IEEE/ACM International Conference on Automation of Software Test AST,
Seoul, 2020, pp. 31–40.
mla: Jovanovikj, Ivan, et al. “Validating Test Case Migration via Mutation Analysis
.” Proceedings of the 1st IEEE/ACM International Conference on Automation of
Software Test AST, ACM, 2020, pp. 31–40.
short: 'I. Jovanovikj, A. Nagaraj, E. Yigitbas, A. Anjorin, S. Sauer, G. Engels,
in: Proceedings of the 1st IEEE/ACM International Conference on Automation of
Software Test AST, ACM, 2020, pp. 31–40.'
conference:
location: Seoul
name: 1st IEEE/ACM International Conference on Automation of Software Test (AST
2020)
date_created: 2020-03-09T13:11:25Z
date_updated: 2022-01-06T06:52:47Z
department:
- _id: '66'
- _id: '534'
language:
- iso: eng
page: 31-40
publication: Proceedings of the 1st IEEE/ACM International Conference on Automation
of Software Test AST
publisher: ACM
status: public
title: 'Validating Test Case Migration via Mutation Analysis '
type: conference
user_id: '8447'
year: '2020'
...
---
_id: '16278'
abstract:
- lang: eng
text: Currently, the coexistence of multiple users and devices challenges the network's
ability to reliably connect them. This article proposes a novel communication
architecture that satisfies the requirements of fifth-generation (5G) mobile network
applications. In particular, this architecture extends and combines ultra-dense
networking (UDN), multi-access edge computing (MEC), and virtual infrastructure
manager (VIM) concepts to provide a flexible network of moving radio access (RA)
nodes, flying or moving to areas where users and devices struggle for connectivity
and data rate. Furthermore, advances in radio communications and non-orthogonal
multiple access (NOMA), virtualization technologies and energy-awareness mechanisms
are integrated towards a mobile UDN that not only allows RA nodes to follow the
user but also enables the virtualized network functions (VNFs) to adapt to user
mobility by migrating from one node to another. Performance evaluation shows that
the underlying network improves connectivity of users and devices through the
flexible deployment of moving RA nodes and the use of NOMA.
article_number: '100250'
author:
- first_name: Nikolaos
full_name: Nomikos, Nikolaos
last_name: Nomikos
- first_name: Emmanouel T.
full_name: Michailidis, Emmanouel T.
last_name: Michailidis
- first_name: Panagiotis
full_name: Trakadas, Panagiotis
last_name: Trakadas
- first_name: Demosthenes
full_name: Vouyioukas, Demosthenes
last_name: Vouyioukas
- first_name: Holger
full_name: Karl, Holger
id: '126'
last_name: Karl
- first_name: Josep
full_name: Martrat, Josep
last_name: Martrat
- first_name: Theodore
full_name: Zahariadis, Theodore
last_name: Zahariadis
- first_name: Konstantinos
full_name: Papadopoulos, Konstantinos
last_name: Papadopoulos
- first_name: Stamatis
full_name: Voliotis, Stamatis
last_name: Voliotis
citation:
ama: Nomikos N, Michailidis ET, Trakadas P, et al. A UAV-based moving 5G RAN for
massive connectivity of mobile users and IoT devices. Vehicular Communications.
2020. doi:10.1016/j.vehcom.2020.100250
apa: Nomikos, N., Michailidis, E. T., Trakadas, P., Vouyioukas, D., Karl, H., Martrat,
J., … Voliotis, S. (2020). A UAV-based moving 5G RAN for massive connectivity
of mobile users and IoT devices. Vehicular Communications. https://doi.org/10.1016/j.vehcom.2020.100250
bibtex: '@article{Nomikos_Michailidis_Trakadas_Vouyioukas_Karl_Martrat_Zahariadis_Papadopoulos_Voliotis_2020,
title={A UAV-based moving 5G RAN for massive connectivity of mobile users and
IoT devices}, DOI={10.1016/j.vehcom.2020.100250},
number={100250}, journal={Vehicular Communications}, author={Nomikos, Nikolaos
and Michailidis, Emmanouel T. and Trakadas, Panagiotis and Vouyioukas, Demosthenes
and Karl, Holger and Martrat, Josep and Zahariadis, Theodore and Papadopoulos,
Konstantinos and Voliotis, Stamatis}, year={2020} }'
chicago: Nomikos, Nikolaos, Emmanouel T. Michailidis, Panagiotis Trakadas, Demosthenes
Vouyioukas, Holger Karl, Josep Martrat, Theodore Zahariadis, Konstantinos Papadopoulos,
and Stamatis Voliotis. “A UAV-Based Moving 5G RAN for Massive Connectivity of
Mobile Users and IoT Devices.” Vehicular Communications, 2020. https://doi.org/10.1016/j.vehcom.2020.100250.
ieee: N. Nomikos et al., “A UAV-based moving 5G RAN for massive connectivity
of mobile users and IoT devices,” Vehicular Communications, 2020.
mla: Nomikos, Nikolaos, et al. “A UAV-Based Moving 5G RAN for Massive Connectivity
of Mobile Users and IoT Devices.” Vehicular Communications, 100250, 2020,
doi:10.1016/j.vehcom.2020.100250.
short: N. Nomikos, E.T. Michailidis, P. Trakadas, D. Vouyioukas, H. Karl, J. Martrat,
T. Zahariadis, K. Papadopoulos, S. Voliotis, Vehicular Communications (2020).
date_created: 2020-03-10T15:59:56Z
date_updated: 2022-01-06T06:52:48Z
department:
- _id: '75'
doi: 10.1016/j.vehcom.2020.100250
language:
- iso: eng
publication: Vehicular Communications
publication_identifier:
issn:
- 2214-2096
publication_status: published
status: public
title: A UAV-based moving 5G RAN for massive connectivity of mobile users and IoT
devices
type: journal_article
user_id: '126'
year: '2020'
...
---
_id: '16280'
abstract:
- lang: eng
text: 'Assigning bands of the wireless spectrum as resources to users is a common
problem in wireless networks. Typically, frequency bands were assumed to be available
in a stable manner. Nevertheless, in recent scenarios where wireless networks
may be deployed in unknown environments, spectrum competition is considered, making
it uncertain whether a frequency band is available at all or at what quality.
To fully exploit such resources with uncertain availability, the multi-armed bandit
(MAB) method, a representative online learning technique, has been applied to
design spectrum scheduling algorithms. This article surveys such proposals. We
describe the following three aspects: how to model spectrum scheduling problems
within the MAB framework, what the main thread is following which prevalent algorithms
are designed, and how to evaluate algorithm performance and complexity. We also
give some promising directions for future research in related fields.'
author:
- first_name: Feng
full_name: Li, Feng
last_name: Li
- first_name: Dongxiao
full_name: Yu, Dongxiao
last_name: Yu
- first_name: Huan
full_name: Yang, Huan
last_name: Yang
- first_name: Jiguo
full_name: Yu, Jiguo
last_name: Yu
- first_name: Holger
full_name: Karl, Holger
id: '126'
last_name: Karl
- first_name: Xiuzhen
full_name: Cheng, Xiuzhen
last_name: Cheng
citation:
ama: 'Li F, Yu D, Yang H, Yu J, Karl H, Cheng X. Multi-Armed-Bandit-Based Spectrum
Scheduling Algorithms in Wireless Networks: A Survey. IEEE Wireless Communications.
2020:24-30. doi:10.1109/mwc.001.1900280'
apa: 'Li, F., Yu, D., Yang, H., Yu, J., Karl, H., & Cheng, X. (2020). Multi-Armed-Bandit-Based
Spectrum Scheduling Algorithms in Wireless Networks: A Survey. IEEE Wireless
Communications, 24–30. https://doi.org/10.1109/mwc.001.1900280'
bibtex: '@article{Li_Yu_Yang_Yu_Karl_Cheng_2020, title={Multi-Armed-Bandit-Based
Spectrum Scheduling Algorithms in Wireless Networks: A Survey}, DOI={10.1109/mwc.001.1900280},
journal={IEEE Wireless Communications}, author={Li, Feng and Yu, Dongxiao and
Yang, Huan and Yu, Jiguo and Karl, Holger and Cheng, Xiuzhen}, year={2020}, pages={24–30}
}'
chicago: 'Li, Feng, Dongxiao Yu, Huan Yang, Jiguo Yu, Holger Karl, and Xiuzhen Cheng.
“Multi-Armed-Bandit-Based Spectrum Scheduling Algorithms in Wireless Networks:
A Survey.” IEEE Wireless Communications, 2020, 24–30. https://doi.org/10.1109/mwc.001.1900280.'
ieee: 'F. Li, D. Yu, H. Yang, J. Yu, H. Karl, and X. Cheng, “Multi-Armed-Bandit-Based
Spectrum Scheduling Algorithms in Wireless Networks: A Survey,” IEEE Wireless
Communications, pp. 24–30, 2020.'
mla: 'Li, Feng, et al. “Multi-Armed-Bandit-Based Spectrum Scheduling Algorithms
in Wireless Networks: A Survey.” IEEE Wireless Communications, 2020, pp.
24–30, doi:10.1109/mwc.001.1900280.'
short: F. Li, D. Yu, H. Yang, J. Yu, H. Karl, X. Cheng, IEEE Wireless Communications
(2020) 24–30.
date_created: 2020-03-10T16:02:30Z
date_updated: 2022-01-06T06:52:48Z
department:
- _id: '75'
doi: 10.1109/mwc.001.1900280
language:
- iso: eng
page: 24-30
publication: IEEE Wireless Communications
publication_identifier:
issn:
- 1536-1284
- 1558-0687
publication_status: published
status: public
title: 'Multi-Armed-Bandit-Based Spectrum Scheduling Algorithms in Wireless Networks:
A Survey'
type: journal_article
user_id: '126'
year: '2020'
...
---
_id: '16288'
abstract:
- lang: eng
text: We derive a data-driven method for the approximation of the Koopman generator
called gEDMD, which can be regarded as a straightforward extension of EDMD (extended
dynamic mode decomposition). This approach is applicable to deterministic and
stochastic dynamical systems. It can be used for computing eigenvalues, eigenfunctions,
and modes of the generator and for system identification. In addition to learning
the governing equations of deterministic systems, which then reduces to SINDy
(sparse identification of nonlinear dynamics), it is possible to identify the
drift and diffusion terms of stochastic differential equations from data. Moreover,
we apply gEDMD to derive coarse-grained models of high-dimensional systems, and
also to determine efficient model predictive control strategies. We highlight
relationships with other methods and demonstrate the efficacy of the proposed
methods using several guiding examples and prototypical molecular dynamics problems.
article_number: '132416'
author:
- first_name: Stefan
full_name: Klus, Stefan
last_name: Klus
- first_name: Feliks
full_name: Nüske, Feliks
id: '81513'
last_name: Nüske
orcid: 0000-0003-2444-7889
- first_name: Sebastian
full_name: Peitz, Sebastian
id: '47427'
last_name: Peitz
orcid: https://orcid.org/0000-0002-3389-793X
- first_name: Jan-Hendrik
full_name: Niemann, Jan-Hendrik
last_name: Niemann
- first_name: Cecilia
full_name: Clementi, Cecilia
last_name: Clementi
- first_name: Christof
full_name: Schütte, Christof
last_name: Schütte
citation:
ama: 'Klus S, Nüske F, Peitz S, Niemann J-H, Clementi C, Schütte C. Data-driven
approximation of the Koopman generator: Model reduction, system identification,
and control. Physica D: Nonlinear Phenomena. 2020;406. doi:10.1016/j.physd.2020.132416'
apa: 'Klus, S., Nüske, F., Peitz, S., Niemann, J.-H., Clementi, C., & Schütte,
C. (2020). Data-driven approximation of the Koopman generator: Model reduction,
system identification, and control. Physica D: Nonlinear Phenomena, 406.
https://doi.org/10.1016/j.physd.2020.132416'
bibtex: '@article{Klus_Nüske_Peitz_Niemann_Clementi_Schütte_2020, title={Data-driven
approximation of the Koopman generator: Model reduction, system identification,
and control}, volume={406}, DOI={10.1016/j.physd.2020.132416},
number={132416}, journal={Physica D: Nonlinear Phenomena}, author={Klus, Stefan
and Nüske, Feliks and Peitz, Sebastian and Niemann, Jan-Hendrik and Clementi,
Cecilia and Schütte, Christof}, year={2020} }'
chicago: 'Klus, Stefan, Feliks Nüske, Sebastian Peitz, Jan-Hendrik Niemann, Cecilia
Clementi, and Christof Schütte. “Data-Driven Approximation of the Koopman Generator:
Model Reduction, System Identification, and Control.” Physica D: Nonlinear
Phenomena 406 (2020). https://doi.org/10.1016/j.physd.2020.132416.'
ieee: 'S. Klus, F. Nüske, S. Peitz, J.-H. Niemann, C. Clementi, and C. Schütte,
“Data-driven approximation of the Koopman generator: Model reduction, system identification,
and control,” Physica D: Nonlinear Phenomena, vol. 406, 2020.'
mla: 'Klus, Stefan, et al. “Data-Driven Approximation of the Koopman Generator:
Model Reduction, System Identification, and Control.” Physica D: Nonlinear
Phenomena, vol. 406, 132416, 2020, doi:10.1016/j.physd.2020.132416.'
short: 'S. Klus, F. Nüske, S. Peitz, J.-H. Niemann, C. Clementi, C. Schütte, Physica
D: Nonlinear Phenomena 406 (2020).'
date_created: 2020-03-13T12:35:40Z
date_updated: 2022-01-06T06:52:48Z
department:
- _id: '101'
doi: 10.1016/j.physd.2020.132416
intvolume: ' 406'
language:
- iso: eng
publication: 'Physica D: Nonlinear Phenomena'
publication_identifier:
issn:
- 0167-2789
publication_status: published
status: public
title: 'Data-driven approximation of the Koopman generator: Model reduction, system
identification, and control'
type: journal_article
user_id: '47427'
volume: 406
year: '2020'
...
---
_id: '16289'
abstract:
- lang: eng
text: In the development of model predictive controllers for PDE-constrained problems,
the use of reduced order models is essential to enable real-time applicability.
Besides local linearization approaches, proper orthogonal decomposition (POD)
has been most widely used in the past in order to derive such models. Due to the
huge advances concerning both theory as well as the numerical approximation, a
very promising alternative based on the Koopman operator has recently emerged.
In this chapter, we present two control strategies for model predictive control
of nonlinear PDEs using data-efficient approximations of the Koopman operator.
In the first one, the dynamic control system is replaced by a small number of
autonomous systems with different yet constant inputs. The control problem is
consequently transformed into a switching problem. In the second approach, a bilinear
surrogate model is obtained via a convex combination of these autonomous systems.
Using a recent convergence result for extended dynamic mode decomposition (EDMD),
convergence of the reduced objective function can be shown. We study the properties
of these two strategies with respect to solution quality, data requirements, and
complexity of the resulting optimization problem using the 1-dimensional Burgers
equation and the 2-dimensional Navier–Stokes equations as examples. Finally, an
extension for online adaptivity is presented.
author:
- first_name: Sebastian
full_name: Peitz, Sebastian
id: '47427'
last_name: Peitz
orcid: https://orcid.org/0000-0002-3389-793X
- first_name: Stefan
full_name: Klus, Stefan
last_name: Klus
citation:
ama: 'Peitz S, Klus S. Feedback Control of Nonlinear PDEs Using Data-Efficient Reduced
Order Models Based on the Koopman Operator. In: Lecture Notes in Control and
Information Sciences. Vol 484. Lecture Notes in Control and Information Sciences.
Cham: Springer; 2020:257-282. doi:10.1007/978-3-030-35713-9_10'
apa: 'Peitz, S., & Klus, S. (2020). Feedback Control of Nonlinear PDEs Using
Data-Efficient Reduced Order Models Based on the Koopman Operator. In Lecture
Notes in Control and Information Sciences (Vol. 484, pp. 257–282). Cham: Springer.
https://doi.org/10.1007/978-3-030-35713-9_10'
bibtex: '@inbook{Peitz_Klus_2020, place={Cham}, series={Lecture Notes in Control
and Information Sciences}, title={Feedback Control of Nonlinear PDEs Using Data-Efficient
Reduced Order Models Based on the Koopman Operator}, volume={484}, DOI={10.1007/978-3-030-35713-9_10},
booktitle={Lecture Notes in Control and Information Sciences}, publisher={Springer},
author={Peitz, Sebastian and Klus, Stefan}, year={2020}, pages={257–282}, collection={Lecture
Notes in Control and Information Sciences} }'
chicago: 'Peitz, Sebastian, and Stefan Klus. “Feedback Control of Nonlinear PDEs
Using Data-Efficient Reduced Order Models Based on the Koopman Operator.” In Lecture
Notes in Control and Information Sciences, 484:257–82. Lecture Notes in Control
and Information Sciences. Cham: Springer, 2020. https://doi.org/10.1007/978-3-030-35713-9_10.'
ieee: 'S. Peitz and S. Klus, “Feedback Control of Nonlinear PDEs Using Data-Efficient
Reduced Order Models Based on the Koopman Operator,” in Lecture Notes in Control
and Information Sciences, vol. 484, Cham: Springer, 2020, pp. 257–282.'
mla: Peitz, Sebastian, and Stefan Klus. “Feedback Control of Nonlinear PDEs Using
Data-Efficient Reduced Order Models Based on the Koopman Operator.” Lecture
Notes in Control and Information Sciences, vol. 484, Springer, 2020, pp. 257–82,
doi:10.1007/978-3-030-35713-9_10.
short: 'S. Peitz, S. Klus, in: Lecture Notes in Control and Information Sciences,
Springer, Cham, 2020, pp. 257–282.'
date_created: 2020-03-13T12:38:52Z
date_updated: 2022-01-06T06:52:48Z
department:
- _id: '101'
doi: 10.1007/978-3-030-35713-9_10
intvolume: ' 484'
language:
- iso: eng
page: 257-282
place: Cham
publication: Lecture Notes in Control and Information Sciences
publication_identifier:
isbn:
- '9783030357122'
- '9783030357139'
issn:
- 0170-8643
- 1610-7411
publication_status: published
publisher: Springer
series_title: Lecture Notes in Control and Information Sciences
status: public
title: Feedback Control of Nonlinear PDEs Using Data-Efficient Reduced Order Models
Based on the Koopman Operator
type: book_chapter
user_id: '47427'
volume: 484
year: '2020'
...
---
_id: '16290'
abstract:
- lang: eng
text: The control of complex systems is of critical importance in many branches
of science, engineering, and industry, many of which are governed by nonlinear
partial differential equations. Controlling an unsteady fluid flow is particularly
important, as flow control is a key enabler for technologies in energy (e.g.,
wind, tidal, and combustion), transportation (e.g., planes, trains, and automobiles),
security (e.g., tracking airborne contamination), and health (e.g., artificial
hearts and artificial respiration). However, the high-dimensional, nonlinear,
and multi-scale dynamics make real-time feedback control infeasible. Fortunately,
these high- dimensional systems exhibit dominant, low-dimensional patterns of
activity that can be exploited for effective control in the sense that knowledge
of the entire state of a system is not required. Advances in machine learning
have the potential to revolutionize flow control given its ability to extract
principled, low-rank feature spaces characterizing such complex systems.We present
a novel deep learning modelpredictive control framework that exploits low-rank
features of the flow in order to achieve considerable improvements to control
performance. Instead of predicting the entire fluid state, we use a recurrent
neural network (RNN) to accurately predict the control relevant quantities of
the system, which are then embedded into an MPC framework to construct a feedback
loop. In order to lower the data requirements and to improve the prediction accuracy
and thus the control performance, incoming sensor data are used to update the
RNN online. The results are validated using varying fluid flow examples of increasing
complexity.
article_type: original
author:
- first_name: Katharina
full_name: Bieker, Katharina
id: '32829'
last_name: Bieker
- first_name: Sebastian
full_name: Peitz, Sebastian
id: '47427'
last_name: Peitz
orcid: https://orcid.org/0000-0002-3389-793X
- first_name: Steven L.
full_name: Brunton, Steven L.
last_name: Brunton
- first_name: J. Nathan
full_name: Kutz, J. Nathan
last_name: Kutz
- first_name: Michael
full_name: Dellnitz, Michael
last_name: Dellnitz
citation:
ama: Bieker K, Peitz S, Brunton SL, Kutz JN, Dellnitz M. Deep model predictive flow
control with limited sensor data and online learning. Theoretical and Computational
Fluid Dynamics. 2020;34:577–591. doi:10.1007/s00162-020-00520-4
apa: Bieker, K., Peitz, S., Brunton, S. L., Kutz, J. N., & Dellnitz, M. (2020).
Deep model predictive flow control with limited sensor data and online learning.
Theoretical and Computational Fluid Dynamics, 34, 577–591. https://doi.org/10.1007/s00162-020-00520-4
bibtex: '@article{Bieker_Peitz_Brunton_Kutz_Dellnitz_2020, title={Deep model predictive
flow control with limited sensor data and online learning}, volume={34}, DOI={10.1007/s00162-020-00520-4},
journal={Theoretical and Computational Fluid Dynamics}, author={Bieker, Katharina
and Peitz, Sebastian and Brunton, Steven L. and Kutz, J. Nathan and Dellnitz,
Michael}, year={2020}, pages={577–591} }'
chicago: 'Bieker, Katharina, Sebastian Peitz, Steven L. Brunton, J. Nathan Kutz,
and Michael Dellnitz. “Deep Model Predictive Flow Control with Limited Sensor
Data and Online Learning.” Theoretical and Computational Fluid Dynamics
34 (2020): 577–591. https://doi.org/10.1007/s00162-020-00520-4.'
ieee: K. Bieker, S. Peitz, S. L. Brunton, J. N. Kutz, and M. Dellnitz, “Deep model
predictive flow control with limited sensor data and online learning,” Theoretical
and Computational Fluid Dynamics, vol. 34, pp. 577–591, 2020.
mla: Bieker, Katharina, et al. “Deep Model Predictive Flow Control with Limited
Sensor Data and Online Learning.” Theoretical and Computational Fluid Dynamics,
vol. 34, 2020, pp. 577–591, doi:10.1007/s00162-020-00520-4.
short: K. Bieker, S. Peitz, S.L. Brunton, J.N. Kutz, M. Dellnitz, Theoretical and
Computational Fluid Dynamics 34 (2020) 577–591.
date_created: 2020-03-13T12:40:09Z
date_updated: 2022-01-06T06:52:48Z
department:
- _id: '101'
doi: 10.1007/s00162-020-00520-4
intvolume: ' 34'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://link.springer.com/content/pdf/10.1007/s00162-020-00520-4.pdf
oa: '1'
page: 577–591
project:
- _id: '52'
name: Computing Resources Provided by the Paderborn Center for Parallel Computing
publication: Theoretical and Computational Fluid Dynamics
publication_identifier:
issn:
- 0935-4964
- 1432-2250
publication_status: published
status: public
title: Deep model predictive flow control with limited sensor data and online learning
type: journal_article
user_id: '47427'
volume: 34
year: '2020'
...
---
_id: '16299'
author:
- first_name: Jannik
full_name: Castenow, Jannik
id: '38705'
last_name: Castenow
- first_name: Matthias
full_name: Fischer, Matthias
id: '146'
last_name: Fischer
- first_name: Jonas
full_name: Harbig, Jonas
last_name: Harbig
- first_name: Daniel
full_name: Jung, Daniel
id: '37827'
last_name: Jung
- first_name: Friedhelm
full_name: Meyer auf der Heide, Friedhelm
id: '15523'
last_name: Meyer auf der Heide
citation:
ama: Castenow J, Fischer M, Harbig J, Jung D, Meyer auf der Heide F. Gathering Anonymous,
Oblivious Robots on a Grid. Theoretical Computer Science. 2020;815:289-309.
doi:10.1016/j.tcs.2020.02.018
apa: Castenow, J., Fischer, M., Harbig, J., Jung, D., & Meyer auf der Heide,
F. (2020). Gathering Anonymous, Oblivious Robots on a Grid. Theoretical Computer
Science, 815, 289–309. https://doi.org/10.1016/j.tcs.2020.02.018
bibtex: '@article{Castenow_Fischer_Harbig_Jung_Meyer auf der Heide_2020, title={Gathering
Anonymous, Oblivious Robots on a Grid}, volume={815}, DOI={10.1016/j.tcs.2020.02.018},
journal={Theoretical Computer Science}, author={Castenow, Jannik and Fischer,
Matthias and Harbig, Jonas and Jung, Daniel and Meyer auf der Heide, Friedhelm},
year={2020}, pages={289–309} }'
chicago: 'Castenow, Jannik, Matthias Fischer, Jonas Harbig, Daniel Jung, and Friedhelm
Meyer auf der Heide. “Gathering Anonymous, Oblivious Robots on a Grid.” Theoretical
Computer Science 815 (2020): 289–309. https://doi.org/10.1016/j.tcs.2020.02.018.'
ieee: J. Castenow, M. Fischer, J. Harbig, D. Jung, and F. Meyer auf der Heide, “Gathering
Anonymous, Oblivious Robots on a Grid,” Theoretical Computer Science, vol.
815, pp. 289–309, 2020.
mla: Castenow, Jannik, et al. “Gathering Anonymous, Oblivious Robots on a Grid.”
Theoretical Computer Science, vol. 815, 2020, pp. 289–309, doi:10.1016/j.tcs.2020.02.018.
short: J. Castenow, M. Fischer, J. Harbig, D. Jung, F. Meyer auf der Heide, Theoretical
Computer Science 815 (2020) 289–309.
date_created: 2020-03-13T12:55:53Z
date_updated: 2022-01-06T06:52:48Z
department:
- _id: '63'
doi: 10.1016/j.tcs.2020.02.018
intvolume: ' 815'
language:
- iso: eng
page: 289-309
publication: Theoretical Computer Science
publication_identifier:
issn:
- 0304-3975
publication_status: published
status: public
title: Gathering Anonymous, Oblivious Robots on a Grid
type: journal_article
user_id: '38705'
volume: 815
year: '2020'
...
---
_id: '16309'
abstract:
- lang: eng
text: "In recent years, the success of the Koopman operator in dynamical systems\r\nanalysis
has also fueled the development of Koopman operator-based control\r\nframeworks.
In order to preserve the relatively low data requirements for an\r\napproximation
via Dynamic Mode Decomposition, a quantization approach was\r\nrecently proposed
in [Peitz & Klus, Automatica 106, 2019]. This way, control\r\nof nonlinear dynamical
systems can be realized by means of switched systems\r\ntechniques, using only
a finite set of autonomous Koopman operator-based\r\nreduced models. These individual
systems can be approximated very efficiently\r\nfrom data. The main idea is to
transform a control system into a set of\r\nautonomous systems for which the optimal
switching sequence has to be computed.\r\nIn this article, we extend these results
to continuous control inputs using\r\nrelaxation. This way, we combine the advantages
of the data efficiency of\r\napproximating a finite set of autonomous systems
with continuous controls. We\r\nshow that when using the Koopman generator, this
relaxation --- realized by\r\nlinear interpolation between two operators --- does
not introduce any error for\r\ncontrol affine systems. This allows us to control
high-dimensional nonlinear\r\nsystems using bilinear, low-dimensional surrogate
models. The efficiency of the\r\nproposed approach is demonstrated using several
examples with increasing\r\ncomplexity, from the Duffing oscillator to the chaotic
fluidic pinball."
author:
- first_name: Sebastian
full_name: Peitz, Sebastian
id: '47427'
last_name: Peitz
orcid: 0000-0002-3389-793X
- first_name: Samuel E.
full_name: Otto, Samuel E.
last_name: Otto
- first_name: Clarence W.
full_name: Rowley, Clarence W.
last_name: Rowley
citation:
ama: Peitz S, Otto SE, Rowley CW. Data-Driven Model Predictive Control using Interpolated
Koopman Generators. SIAM Journal on Applied Dynamical Systems. 2020;19(3):2162-2193.
doi:10.1137/20M1325678
apa: Peitz, S., Otto, S. E., & Rowley, C. W. (2020). Data-Driven Model Predictive
Control using Interpolated Koopman Generators. SIAM Journal on Applied Dynamical
Systems, 19(3), 2162–2193. https://doi.org/10.1137/20M1325678
bibtex: '@article{Peitz_Otto_Rowley_2020, title={Data-Driven Model Predictive Control
using Interpolated Koopman Generators}, volume={19}, DOI={10.1137/20M1325678},
number={3}, journal={SIAM Journal on Applied Dynamical Systems}, author={Peitz,
Sebastian and Otto, Samuel E. and Rowley, Clarence W.}, year={2020}, pages={2162–2193}
}'
chicago: 'Peitz, Sebastian, Samuel E. Otto, and Clarence W. Rowley. “Data-Driven
Model Predictive Control Using Interpolated Koopman Generators.” SIAM Journal
on Applied Dynamical Systems 19, no. 3 (2020): 2162–93. https://doi.org/10.1137/20M1325678.'
ieee: S. Peitz, S. E. Otto, and C. W. Rowley, “Data-Driven Model Predictive Control
using Interpolated Koopman Generators,” SIAM Journal on Applied Dynamical
Systems, vol. 19, no. 3, pp. 2162–2193, 2020.
mla: Peitz, Sebastian, et al. “Data-Driven Model Predictive Control Using Interpolated
Koopman Generators.” SIAM Journal on Applied Dynamical Systems, vol. 19,
no. 3, 2020, pp. 2162–93, doi:10.1137/20M1325678.
short: S. Peitz, S.E. Otto, C.W. Rowley, SIAM Journal on Applied Dynamical Systems
19 (2020) 2162–2193.
date_created: 2020-03-17T09:53:01Z
date_updated: 2022-01-06T06:52:48Z
department:
- _id: '101'
doi: 10.1137/20M1325678
intvolume: ' 19'
issue: '3'
language:
- iso: eng
main_file_link:
- url: https://epubs.siam.org/doi/pdf/10.1137/20M1325678
page: 2162-2193
publication: SIAM Journal on Applied Dynamical Systems
status: public
title: Data-Driven Model Predictive Control using Interpolated Koopman Generators
type: journal_article
user_id: '47427'
volume: 19
year: '2020'
...
---
_id: '16363'
author:
- first_name: Tim
full_name: Hansmeier, Tim
id: '49992'
last_name: Hansmeier
orcid: 0000-0003-1377-3339
- first_name: Paul
full_name: Kaufmann, Paul
last_name: Kaufmann
- first_name: Marco
full_name: Platzner, Marco
id: '398'
last_name: Platzner
citation:
ama: 'Hansmeier T, Kaufmann P, Platzner M. Enabling XCSF to Cope with Dynamic Environments
via an Adaptive Error Threshold. In: GECCO ’20: Proceedings of the Genetic
and Evolutionary Computation Conference Companion. New York, NY, United States:
Association for Computing Machinery (ACM); 2020:125-126. doi:10.1145/3377929.3389968'
apa: 'Hansmeier, T., Kaufmann, P., & Platzner, M. (2020). Enabling XCSF to Cope
with Dynamic Environments via an Adaptive Error Threshold. In GECCO ’20: Proceedings
of the Genetic and Evolutionary Computation Conference Companion (pp. 125–126).
New York, NY, United States: Association for Computing Machinery (ACM). https://doi.org/10.1145/3377929.3389968'
bibtex: '@inproceedings{Hansmeier_Kaufmann_Platzner_2020, place={New York, NY, United
States}, title={Enabling XCSF to Cope with Dynamic Environments via an Adaptive
Error Threshold}, DOI={10.1145/3377929.3389968},
booktitle={GECCO ’20: Proceedings of the Genetic and Evolutionary Computation
Conference Companion}, publisher={Association for Computing Machinery (ACM)},
author={Hansmeier, Tim and Kaufmann, Paul and Platzner, Marco}, year={2020}, pages={125–126}
}'
chicago: 'Hansmeier, Tim, Paul Kaufmann, and Marco Platzner. “Enabling XCSF to Cope
with Dynamic Environments via an Adaptive Error Threshold.” In GECCO ’20: Proceedings
of the Genetic and Evolutionary Computation Conference Companion, 125–26.
New York, NY, United States: Association for Computing Machinery (ACM), 2020.
https://doi.org/10.1145/3377929.3389968.'
ieee: 'T. Hansmeier, P. Kaufmann, and M. Platzner, “Enabling XCSF to Cope with Dynamic
Environments via an Adaptive Error Threshold,” in GECCO ’20: Proceedings of
the Genetic and Evolutionary Computation Conference Companion, Cancún, Mexico,
2020, pp. 125–126.'
mla: 'Hansmeier, Tim, et al. “Enabling XCSF to Cope with Dynamic Environments via
an Adaptive Error Threshold.” GECCO ’20: Proceedings of the Genetic and Evolutionary
Computation Conference Companion, Association for Computing Machinery (ACM),
2020, pp. 125–26, doi:10.1145/3377929.3389968.'
short: 'T. Hansmeier, P. Kaufmann, M. Platzner, in: GECCO ’20: Proceedings of the
Genetic and Evolutionary Computation Conference Companion, Association for Computing
Machinery (ACM), New York, NY, United States, 2020, pp. 125–126.'
conference:
end_date: 2020-07-12
location: Cancún, Mexico
name: The Genetic and Evolutionary Computation Conference (GECCO 2020)
start_date: 2020-07-08
date_created: 2020-04-02T10:07:10Z
date_updated: 2022-01-06T06:52:49Z
department:
- _id: '78'
doi: 10.1145/3377929.3389968
language:
- iso: eng
page: 125-126
place: New York, NY, United States
project:
- _id: '4'
name: SFB 901 - Project Area C
- _id: '1'
name: SFB 901
- _id: '14'
name: SFB 901 - Subproject C2
publication: 'GECCO ''20: Proceedings of the Genetic and Evolutionary Computation
Conference Companion'
publication_identifier:
isbn:
- 978-1-4503-7127-8
publication_status: published
publisher: Association for Computing Machinery (ACM)
status: public
title: Enabling XCSF to Cope with Dynamic Environments via an Adaptive Error Threshold
type: conference
user_id: '477'
year: '2020'
...
---
_id: '16400'
abstract:
- lang: eng
text: "Softwarization facilitates the introduction of smart\r\nmanufacturing applications
in the industry. Manifold devices\r\nsuch as machine computers, Industrial IoT
devices, tablets,\r\nsmartphones and smart glasses are integrated into factory
networks\r\nto enable shop floor digitalization and big data analysis. To\r\nhandle
the increasing number of devices and the resulting traffic,\r\na flexible and
scalable factory network is necessary which can be\r\nrealized using softwarization
technologies like Network Function\r\nVirtualization (NFV). However, the security
risks increase with\r\nthe increasing number of new devices, so that cyber security
must\r\nalso be considered in NFV-based networks.\r\n\r\nTherefore, extending
our previous work, we showcase threat\r\ndetection using a cloud-native NFV-driven
intrusion detection\r\nsystem (IDS) that is integrated in our industrial-specific
network\r\nservices. As a result of the threat detection, the affected network\r\nservice
is put into quarantine via automatic network reconfiguration.\r\nWe use the 5GTANGO
service platform to deploy our\r\ndeveloped network services on Kubernetes and
to initiate the\r\nnetwork reconfiguration."
author:
- first_name: Marcel
full_name: Müller, Marcel
last_name: Müller
- first_name: Daniel
full_name: Behnke, Daniel
last_name: Behnke
- first_name: Patrick-Benjamin
full_name: Bök, Patrick-Benjamin
last_name: Bök
- first_name: Stefan Balthasar
full_name: Schneider, Stefan Balthasar
id: '35343'
last_name: Schneider
orcid: 0000-0001-8210-4011
- first_name: Manuel
full_name: Peuster, Manuel
id: '13271'
last_name: Peuster
- first_name: Holger
full_name: Karl, Holger
id: '126'
last_name: Karl
citation:
ama: 'Müller M, Behnke D, Bök P-B, Schneider SB, Peuster M, Karl H. Cloud-Native
Threat Detection and Containment for Smart Manufacturing. In: IEEE Conference
on Network Softwarization (NetSoft) Demo Track. Ghent, Belgium: IEEE; 2020.'
apa: 'Müller, M., Behnke, D., Bök, P.-B., Schneider, S. B., Peuster, M., & Karl,
H. (2020). Cloud-Native Threat Detection and Containment for Smart Manufacturing.
In IEEE Conference on Network Softwarization (NetSoft) Demo Track. Ghent,
Belgium: IEEE.'
bibtex: '@inproceedings{Müller_Behnke_Bök_Schneider_Peuster_Karl_2020, place={Ghent,
Belgium}, title={Cloud-Native Threat Detection and Containment for Smart Manufacturing},
booktitle={IEEE Conference on Network Softwarization (NetSoft) Demo Track}, publisher={IEEE},
author={Müller, Marcel and Behnke, Daniel and Bök, Patrick-Benjamin and Schneider,
Stefan Balthasar and Peuster, Manuel and Karl, Holger}, year={2020} }'
chicago: 'Müller, Marcel, Daniel Behnke, Patrick-Benjamin Bök, Stefan Balthasar
Schneider, Manuel Peuster, and Holger Karl. “Cloud-Native Threat Detection and
Containment for Smart Manufacturing.” In IEEE Conference on Network Softwarization
(NetSoft) Demo Track. Ghent, Belgium: IEEE, 2020.'
ieee: M. Müller, D. Behnke, P.-B. Bök, S. B. Schneider, M. Peuster, and H. Karl,
“Cloud-Native Threat Detection and Containment for Smart Manufacturing,” in IEEE
Conference on Network Softwarization (NetSoft) Demo Track, Ghent, Belgium,
2020.
mla: Müller, Marcel, et al. “Cloud-Native Threat Detection and Containment for Smart
Manufacturing.” IEEE Conference on Network Softwarization (NetSoft) Demo Track,
IEEE, 2020.
short: 'M. Müller, D. Behnke, P.-B. Bök, S.B. Schneider, M. Peuster, H. Karl, in:
IEEE Conference on Network Softwarization (NetSoft) Demo Track, IEEE, Ghent, Belgium,
2020.'
conference:
location: Ghent, Belgium
name: IEEE Conference on Network Softwarization (NetSoft) Demo Track
date_created: 2020-04-03T11:53:00Z
date_updated: 2022-01-06T06:52:50Z
department:
- _id: '75'
language:
- iso: eng
place: Ghent, Belgium
project:
- _id: '28'
grant_number: '761493'
name: 5G Development and validation platform for global industry-specific network
services and Apps
- _id: '1'
name: SFB 901
- _id: '4'
name: SFB 901 - Project Area C
- _id: '16'
name: SFB 901 - Subproject C4
publication: IEEE Conference on Network Softwarization (NetSoft) Demo Track
publisher: IEEE
status: public
title: Cloud-Native Threat Detection and Containment for Smart Manufacturing
type: conference
user_id: '35343'
year: '2020'
...
---
_id: '13868'
author:
- first_name: Simon
full_name: Pukrop, Simon
id: '44428'
last_name: Pukrop
- first_name: Alexander
full_name: Mäcker, Alexander
id: '13536'
last_name: Mäcker
- first_name: Friedhelm
full_name: Meyer auf der Heide, Friedhelm
id: '15523'
last_name: Meyer auf der Heide
citation:
ama: 'Pukrop S, Mäcker A, Meyer auf der Heide F. Approximating Weighted Completion
Time for Order Scheduling with Setup Times. In: Proceedings of the 46th International
Conference on Current Trends in Theory and Practice of Computer Science (SOFSEM).
; 2020.'
apa: Pukrop, S., Mäcker, A., & Meyer auf der Heide, F. (2020). Approximating
Weighted Completion Time for Order Scheduling with Setup Times. In Proceedings
of the 46th International Conference on Current Trends in Theory and Practice
of Computer Science (SOFSEM).
bibtex: '@inproceedings{Pukrop_Mäcker_Meyer auf der Heide_2020, title={Approximating
Weighted Completion Time for Order Scheduling with Setup Times}, booktitle={Proceedings
of the 46th International Conference on Current Trends in Theory and Practice
of Computer Science (SOFSEM)}, author={Pukrop, Simon and Mäcker, Alexander and
Meyer auf der Heide, Friedhelm}, year={2020} }'
chicago: Pukrop, Simon, Alexander Mäcker, and Friedhelm Meyer auf der Heide. “Approximating
Weighted Completion Time for Order Scheduling with Setup Times.” In Proceedings
of the 46th International Conference on Current Trends in Theory and Practice
of Computer Science (SOFSEM), 2020.
ieee: S. Pukrop, A. Mäcker, and F. Meyer auf der Heide, “Approximating Weighted
Completion Time for Order Scheduling with Setup Times,” in Proceedings of the
46th International Conference on Current Trends in Theory and Practice of Computer
Science (SOFSEM), 2020.
mla: Pukrop, Simon, et al. “Approximating Weighted Completion Time for Order Scheduling
with Setup Times.” Proceedings of the 46th International Conference on Current
Trends in Theory and Practice of Computer Science (SOFSEM), 2020.
short: 'S. Pukrop, A. Mäcker, F. Meyer auf der Heide, in: Proceedings of the 46th
International Conference on Current Trends in Theory and Practice of Computer
Science (SOFSEM), 2020.'
date_created: 2019-10-15T12:19:49Z
date_updated: 2022-01-06T06:51:45Z
department:
- _id: '63'
language:
- iso: eng
project:
- _id: '4'
name: SFB 901 - Project Area C
- _id: '1'
name: SFB 901
- _id: '16'
name: SFB 901 - Subproject C4
publication: Proceedings of the 46th International Conference on Current Trends in
Theory and Practice of Computer Science (SOFSEM)
status: public
title: Approximating Weighted Completion Time for Order Scheduling with Setup Times
type: conference
user_id: '44428'
year: '2020'
...
---
_id: '13108'
abstract:
- lang: ger
text: Diagrammatisches Schlie{\ss}en wird im Zusammenhang mit dem Lernen von Mathmematik
und ihrer Symbolsprache als wesentliche Theorie der Wissenskonstruktion diskutiert.
Dabei wird h{\"{a}}ufig davon ausgegangen, dass die Wissenskonstruktion im Sinne
diagrammatischen Schlie{\ss}ens erfolgt. Deskriptive Rekonstruktionen diagrammatischen
Schlie{\ss}ens bei Lernenden stellen jedoch ein Desiderat der mathematikdidaktischen
Forschung dar. Der vorliegende Beitrag befasst sich mit der Fragestellung, wie
sich diagrammatisches Schlie{\ss}en bei Lernenden rekonstruieren l{\"{a}}sst.
Als m{\"{o}}gliche Werkzeuge f{\"{u}}r eine solche Rekonstruktion werden Toulmins
Argumentationsschema und Vergnauds Schema-Begriff exemplarisch angewandt, um das
diagrammatische Schlie{\ss}en eines Sch{\"{u}}lerpaars beim Einstieg in die Subtraktion
negativer Zahlen zu rekonstruieren. Abschlie{\ss}end wird die tats{\"{a}}chliche
Eignung der beiden Ans{\"{a}}tze zur Rekonstruktion diagrammatischen Schlie{\ss}ens
diskutiert.
author:
- first_name: Jan
full_name: Schumacher, Jan
id: '26809'
last_name: Schumacher
orcid: 0000-0002-6676-9774
- first_name: Sebastian
full_name: Rezat, Sebastian
last_name: Rezat
citation:
ama: 'Schumacher J, Rezat S. Rekonstruktion diagrammatischen Schließens beim Erlernen
der Subtraktion negativer Zahlen. Vergleich zweier methodischer Zugänge. In: Kadunz
G, ed. Zeichen und Sprache im Mathematikunterricht. Springer; 2020. doi:10.1007/978-3-662-61194-4_5'
apa: Schumacher, J., & Rezat, S. (2020). Rekonstruktion diagrammatischen Schließens
beim Erlernen der Subtraktion negativer Zahlen. Vergleich zweier methodischer
Zugänge. In G. Kadunz (Ed.), Zeichen und Sprache im Mathematikunterricht.
Springer. https://doi.org/10.1007/978-3-662-61194-4_5
bibtex: '@inbook{Schumacher_Rezat_2020, title={Rekonstruktion diagrammatischen Schließens
beim Erlernen der Subtraktion negativer Zahlen. Vergleich zweier methodischer
Zugänge}, DOI={10.1007/978-3-662-61194-4_5},
booktitle={Zeichen und Sprache im Mathematikunterricht}, publisher={Springer},
author={Schumacher, Jan and Rezat, Sebastian}, editor={Kadunz, GertEditor}, year={2020}
}'
chicago: Schumacher, Jan, and Sebastian Rezat. “Rekonstruktion diagrammatischen
Schließens beim Erlernen der Subtraktion negativer Zahlen. Vergleich zweier methodischer
Zugänge.” In Zeichen und Sprache im Mathematikunterricht, edited by Gert
Kadunz. Springer, 2020. https://doi.org/10.1007/978-3-662-61194-4_5.
ieee: J. Schumacher and S. Rezat, “Rekonstruktion diagrammatischen Schließens beim
Erlernen der Subtraktion negativer Zahlen. Vergleich zweier methodischer Zugänge,”
in Zeichen und Sprache im Mathematikunterricht, G. Kadunz, Ed. Springer,
2020.
mla: Schumacher, Jan, and Sebastian Rezat. “Rekonstruktion diagrammatischen Schließens
beim Erlernen der Subtraktion negativer Zahlen. Vergleich zweier methodischer
Zugänge.” Zeichen und Sprache im Mathematikunterricht, edited by Gert Kadunz,
Springer, 2020, doi:10.1007/978-3-662-61194-4_5.
short: 'J. Schumacher, S. Rezat, in: G. Kadunz (Ed.), Zeichen und Sprache im Mathematikunterricht,
Springer, 2020.'
date_created: 2019-08-30T12:00:51Z
date_updated: 2022-01-06T06:51:28Z
department:
- _id: '360'
- _id: '98'
doi: 10.1007/978-3-662-61194-4_5
editor:
- first_name: Gert
full_name: Kadunz, Gert
last_name: Kadunz
language:
- iso: ger
publication: Zeichen und Sprache im Mathematikunterricht
publication_status: published
publisher: Springer
quality_controlled: '1'
status: public
title: Rekonstruktion diagrammatischen Schließens beim Erlernen der Subtraktion negativer
Zahlen. Vergleich zweier methodischer Zugänge
type: book_chapter
user_id: '26809'
year: '2020'
...
---
_id: '10330'
author:
- first_name: Dora
full_name: Kiesel, Dora
last_name: Kiesel
- first_name: Patrick
full_name: Riehmann, Patrick
last_name: Riehmann
- first_name: Henning
full_name: Wachsmuth, Henning
id: '3900'
last_name: Wachsmuth
- first_name: Benno
full_name: Stein, Benno
last_name: Stein
- first_name: Bernd
full_name: Fröhlich, Bernd
last_name: Fröhlich
citation:
ama: Kiesel D, Riehmann P, Wachsmuth H, Stein B, Fröhlich B. Visual Analysis of
Argumentation in Essays. IEEE Transactions of Visualization & Computer
Graphics. 27(2):1139-1148.
apa: Kiesel, D., Riehmann, P., Wachsmuth, H., Stein, B., & Fröhlich, B. (n.d.).
Visual Analysis of Argumentation in Essays. IEEE Transactions of Visualization
& Computer Graphics, 27(2), 1139–1148.
bibtex: '@article{Kiesel_Riehmann_Wachsmuth_Stein_Fröhlich, title={Visual Analysis
of Argumentation in Essays}, volume={27}, number={2}, journal={IEEE Transactions
of Visualization & Computer Graphics}, author={Kiesel, Dora and Riehmann,
Patrick and Wachsmuth, Henning and Stein, Benno and Fröhlich, Bernd}, pages={1139–1148}
}'
chicago: 'Kiesel, Dora, Patrick Riehmann, Henning Wachsmuth, Benno Stein, and Bernd
Fröhlich. “Visual Analysis of Argumentation in Essays.” IEEE Transactions of
Visualization & Computer Graphics 27, no. 2 (n.d.): 1139–48.'
ieee: D. Kiesel, P. Riehmann, H. Wachsmuth, B. Stein, and B. Fröhlich, “Visual Analysis
of Argumentation in Essays,” IEEE Transactions of Visualization & Computer
Graphics, vol. 27, no. 2, pp. 1139–1148.
mla: Kiesel, Dora, et al. “Visual Analysis of Argumentation in Essays.” IEEE
Transactions of Visualization & Computer Graphics, vol. 27, no. 2, pp.
1139–48.
short: D. Kiesel, P. Riehmann, H. Wachsmuth, B. Stein, B. Fröhlich, IEEE Transactions
of Visualization & Computer Graphics 27 (n.d.) 1139–1148.
date_created: 2019-06-27T12:58:13Z
date_updated: 2022-01-06T06:50:37Z
department:
- _id: '600'
intvolume: ' 27'
issue: '2'
language:
- iso: eng
main_file_link:
- url: https://www.uni-weimar.de/fileadmin/user/fak/medien/professuren/Virtual_Reality/documents/publications/Visual_Analysis_of_Argumentation_in_Essays.pdf
page: 1139-1148
publication: IEEE Transactions of Visualization & Computer Graphics
publication_status: accepted
status: public
title: Visual Analysis of Argumentation in Essays
type: journal_article
user_id: '82920'
volume: 27
year: '2020'
...
---
_id: '21252'
author:
- first_name: Arne
full_name: Traue, Arne
last_name: Traue
- first_name: Gerrit
full_name: Book, Gerrit
last_name: Book
- first_name: Wilhelm
full_name: Kirchgässner, Wilhelm
id: '49265'
last_name: Kirchgässner
orcid: 0000-0001-9490-1843
- first_name: Oliver
full_name: Wallscheid, Oliver
id: '11291'
last_name: Wallscheid
orcid: https://orcid.org/0000-0001-9362-8777
citation:
ama: Traue A, Book G, Kirchgässner W, Wallscheid O. Toward a Reinforcement Learning
Environment Toolbox for Intelligent Electric Motor Control. IEEE Transactions
on Neural Networks and Learning Systems. Published online 2020:1-10. doi:10.1109/tnnls.2020.3029573
apa: Traue, A., Book, G., Kirchgässner, W., & Wallscheid, O. (2020). Toward
a Reinforcement Learning Environment Toolbox for Intelligent Electric Motor Control.
IEEE Transactions on Neural Networks and Learning Systems, 1–10. https://doi.org/10.1109/tnnls.2020.3029573
bibtex: '@article{Traue_Book_Kirchgässner_Wallscheid_2020, title={Toward a Reinforcement
Learning Environment Toolbox for Intelligent Electric Motor Control}, DOI={10.1109/tnnls.2020.3029573},
journal={IEEE Transactions on Neural Networks and Learning Systems}, author={Traue,
Arne and Book, Gerrit and Kirchgässner, Wilhelm and Wallscheid, Oliver}, year={2020},
pages={1–10} }'
chicago: Traue, Arne, Gerrit Book, Wilhelm Kirchgässner, and Oliver Wallscheid.
“Toward a Reinforcement Learning Environment Toolbox for Intelligent Electric
Motor Control.” IEEE Transactions on Neural Networks and Learning Systems,
2020, 1–10. https://doi.org/10.1109/tnnls.2020.3029573.
ieee: 'A. Traue, G. Book, W. Kirchgässner, and O. Wallscheid, “Toward a Reinforcement
Learning Environment Toolbox for Intelligent Electric Motor Control,” IEEE
Transactions on Neural Networks and Learning Systems, pp. 1–10, 2020, doi:
10.1109/tnnls.2020.3029573.'
mla: Traue, Arne, et al. “Toward a Reinforcement Learning Environment Toolbox for
Intelligent Electric Motor Control.” IEEE Transactions on Neural Networks and
Learning Systems, 2020, pp. 1–10, doi:10.1109/tnnls.2020.3029573.
short: A. Traue, G. Book, W. Kirchgässner, O. Wallscheid, IEEE Transactions on Neural
Networks and Learning Systems (2020) 1–10.
date_created: 2021-02-16T21:23:53Z
date_updated: 2022-02-18T13:26:18Z
department:
- _id: '52'
doi: 10.1109/tnnls.2020.3029573
language:
- iso: eng
page: 1-10
publication: IEEE Transactions on Neural Networks and Learning Systems
publication_identifier:
issn:
- 2162-237X
- 2162-2388
publication_status: published
status: public
title: Toward a Reinforcement Learning Environment Toolbox for Intelligent Electric
Motor Control
type: journal_article
user_id: '49265'
year: '2020'
...
---
_id: '29884'
author:
- first_name: Joachim
full_name: Böcker, Joachim
id: '66'
last_name: Böcker
orcid: 0000-0002-8480-7295
citation:
ama: 'Böcker J. Analysis of the Magnetic Skin Effekt in Motors and Inductors. In:
2020 International Symposium on Power Electronics, Electrical Drives, Automation
and Motion (SPEEDAM). IEEE; 2020. doi:10.1109/speedam48782.2020.9161895'
apa: Böcker, J. (2020). Analysis of the Magnetic Skin Effekt in Motors and Inductors.
2020 International Symposium on Power Electronics, Electrical Drives, Automation
and Motion (SPEEDAM). SPEEDAM. https://doi.org/10.1109/speedam48782.2020.9161895
bibtex: '@inproceedings{Böcker_2020, title={Analysis of the Magnetic Skin Effekt
in Motors and Inductors}, DOI={10.1109/speedam48782.2020.9161895},
booktitle={2020 International Symposium on Power Electronics, Electrical Drives,
Automation and Motion (SPEEDAM)}, publisher={IEEE}, author={Böcker, Joachim},
year={2020} }'
chicago: Böcker, Joachim. “Analysis of the Magnetic Skin Effekt in Motors and Inductors.”
In 2020 International Symposium on Power Electronics, Electrical Drives, Automation
and Motion (SPEEDAM). IEEE, 2020. https://doi.org/10.1109/speedam48782.2020.9161895.
ieee: 'J. Böcker, “Analysis of the Magnetic Skin Effekt in Motors and Inductors,”
presented at the SPEEDAM, 2020, doi: 10.1109/speedam48782.2020.9161895.'
mla: Böcker, Joachim. “Analysis of the Magnetic Skin Effekt in Motors and Inductors.”
2020 International Symposium on Power Electronics, Electrical Drives, Automation
and Motion (SPEEDAM), IEEE, 2020, doi:10.1109/speedam48782.2020.9161895.
short: 'J. Böcker, in: 2020 International Symposium on Power Electronics, Electrical
Drives, Automation and Motion (SPEEDAM), IEEE, 2020.'
conference:
name: SPEEDAM
start_date: '2020'
date_created: 2022-02-19T09:45:52Z
date_updated: 2022-02-19T10:09:10Z
department:
- _id: '34'
- _id: '52'
doi: 10.1109/speedam48782.2020.9161895
language:
- iso: eng
publication: 2020 International Symposium on Power Electronics, Electrical Drives,
Automation and Motion (SPEEDAM)
publication_status: published
publisher: IEEE
status: public
title: Analysis of the Magnetic Skin Effekt in Motors and Inductors
type: conference
user_id: '66'
year: '2020'
...
---
_id: '19422'
author:
- first_name: Alexander
full_name: Sprenger, Alexander
id: '22707'
last_name: Sprenger
- first_name: Somayeh
full_name: Sadeghi-Kohan, Somayeh
id: '78614'
last_name: Sadeghi-Kohan
- first_name: Jan Dennis
full_name: Reimer, Jan Dennis
id: '36703'
last_name: Reimer
- first_name: Sybille
full_name: Hellebrand, Sybille
id: '209'
last_name: Hellebrand
orcid: 0000-0002-3717-3939
citation:
ama: 'Sprenger A, Sadeghi-Kohan S, Reimer JD, Hellebrand S. Variation-Aware Test
for Logic Interconnects using Neural Networks - A Case Study. In: IEEE International
Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFT’20),
October 2020. ; 2020.'
apa: Sprenger, A., Sadeghi-Kohan, S., Reimer, J. D., & Hellebrand, S. (2020).
Variation-Aware Test for Logic Interconnects using Neural Networks - A Case Study.
IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology
Systems (DFT’20), October 2020.
bibtex: '@inproceedings{Sprenger_Sadeghi-Kohan_Reimer_Hellebrand_2020, place={Virtual
Conference - Originally Frascati (Rome), Italy}, title={Variation-Aware Test for
Logic Interconnects using Neural Networks - A Case Study}, booktitle={IEEE International
Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFT’20),
October 2020}, author={Sprenger, Alexander and Sadeghi-Kohan, Somayeh and Reimer,
Jan Dennis and Hellebrand, Sybille}, year={2020} }'
chicago: Sprenger, Alexander, Somayeh Sadeghi-Kohan, Jan Dennis Reimer, and Sybille
Hellebrand. “Variation-Aware Test for Logic Interconnects Using Neural Networks
- A Case Study.” In IEEE International Symposium on Defect and Fault Tolerance
in VLSI and Nanotechnology Systems (DFT’20), October 2020. Virtual Conference
- Originally Frascati (Rome), Italy, 2020.
ieee: A. Sprenger, S. Sadeghi-Kohan, J. D. Reimer, and S. Hellebrand, “Variation-Aware
Test for Logic Interconnects using Neural Networks - A Case Study,” 2020.
mla: Sprenger, Alexander, et al. “Variation-Aware Test for Logic Interconnects Using
Neural Networks - A Case Study.” IEEE International Symposium on Defect and
Fault Tolerance in VLSI and Nanotechnology Systems (DFT’20), October 2020,
2020.
short: 'A. Sprenger, S. Sadeghi-Kohan, J.D. Reimer, S. Hellebrand, in: IEEE International
Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFT’20),
October 2020, Virtual Conference - Originally Frascati (Rome), Italy, 2020.'
conference:
end_date: 2020-10-21
start_date: 2020-10-19
date_created: 2020-09-15T14:03:02Z
date_updated: 2022-02-19T14:16:58Z
department:
- _id: '48'
language:
- iso: eng
place: Virtual Conference - Originally Frascati (Rome), Italy
publication: IEEE International Symposium on Defect and Fault Tolerance in VLSI and
Nanotechnology Systems (DFT’20), October 2020
publication_status: published
status: public
title: Variation-Aware Test for Logic Interconnects using Neural Networks - A Case
Study
type: conference
user_id: '209'
year: '2020'
...
---
_id: '21250'
author:
- first_name: Wilhelm
full_name: Kirchgässner, Wilhelm
id: '49265'
last_name: Kirchgässner
orcid: 0000-0001-9490-1843
- first_name: Oliver
full_name: Wallscheid, Oliver
id: '11291'
last_name: Wallscheid
orcid: https://orcid.org/0000-0001-9362-8777
- first_name: Joachim
full_name: Böcker, Joachim
id: '66'
last_name: Böcker
orcid: 0000-0002-8480-7295
citation:
ama: Kirchgässner W, Wallscheid O, Böcker J. Estimating Electric Motor Temperatures
with Deep Residual Machine Learning. IEEE Transactions on Power Electronics.
2020;36(7):7480-7488. doi:10.1109/tpel.2020.3045596
apa: Kirchgässner, W., Wallscheid, O., & Böcker, J. (2020). Estimating Electric
Motor Temperatures with Deep Residual Machine Learning. IEEE Transactions on
Power Electronics, 36(7), 7480–7488. https://doi.org/10.1109/tpel.2020.3045596
bibtex: '@article{Kirchgässner_Wallscheid_Böcker_2020, title={Estimating Electric
Motor Temperatures with Deep Residual Machine Learning}, volume={36}, DOI={10.1109/tpel.2020.3045596},
number={7}, journal={IEEE Transactions on Power Electronics}, author={Kirchgässner,
Wilhelm and Wallscheid, Oliver and Böcker, Joachim}, year={2020}, pages={7480–7488}
}'
chicago: 'Kirchgässner, Wilhelm, Oliver Wallscheid, and Joachim Böcker. “Estimating
Electric Motor Temperatures with Deep Residual Machine Learning.” IEEE Transactions
on Power Electronics 36, no. 7 (2020): 7480–88. https://doi.org/10.1109/tpel.2020.3045596.'
ieee: 'W. Kirchgässner, O. Wallscheid, and J. Böcker, “Estimating Electric Motor
Temperatures with Deep Residual Machine Learning,” IEEE Transactions on Power
Electronics, vol. 36, no. 7, pp. 7480–7488, 2020, doi: 10.1109/tpel.2020.3045596.'
mla: Kirchgässner, Wilhelm, et al. “Estimating Electric Motor Temperatures with
Deep Residual Machine Learning.” IEEE Transactions on Power Electronics,
vol. 36, no. 7, 2020, pp. 7480–88, doi:10.1109/tpel.2020.3045596.
short: W. Kirchgässner, O. Wallscheid, J. Böcker, IEEE Transactions on Power Electronics
36 (2020) 7480–7488.
date_created: 2021-02-16T21:22:32Z
date_updated: 2022-02-19T16:51:20Z
department:
- _id: '52'
doi: 10.1109/tpel.2020.3045596
intvolume: ' 36'
issue: '7'
language:
- iso: eng
page: 7480-7488
publication: IEEE Transactions on Power Electronics
publication_identifier:
issn:
- 0885-8993
- 1941-0107
publication_status: published
status: public
title: Estimating Electric Motor Temperatures with Deep Residual Machine Learning
type: journal_article
user_id: '49265'
volume: 36
year: '2020'
...
---
_id: '29939'
abstract:
- lang: eng
text: In this paper, a full-bridge modular multilevel converter (MMC) and two half-bridge-based
MMCs are evaluated for high-current low-voltage e.g. 100 - 400V DC-applications
such as electrolysis, arc welding or datacenters with DC-power distribution. Usually,
modular multilevel converters are used in high-voltage DC-applications (HVDC)
in the multiple kV-range, but to meet the needs of a high-current demand at low
output voltage levels, the modular converter concept requires adaptations. In
the proposed concept, the MMC is used to step-down the three-phase medium-voltage
of 10kV, and provide up to 1 MW to the load. Therefore, each module is extended
by an LLC resonant converter to adapt to the specific electrolyzers DC-voltage
range of 142 - 220V and to provide galvanic isolation. The six-arm MMC converter
with half-bridge modules can be simplified and optimized by removing three arms,
and thus halving the number of modules. In addition, the module voltage ripple
and capacitor losses are decreased by 22% and 30% respectively. By rearranging
the components of the half-bridge MMC to build a MMC consisting of grid-side full-bridge
modules, the voltage ripple is further reduced by 78% and capacitor losses by
64%, while ensuring identical costs and volume for all MMCs. Finally, the LLC
resonant converter is designed for the most efficient full-bridge MMC. The LLC
can not operate at resonance with a fixed nominal module voltage of 770V because
the output voltage is varying between 142 - 220V. By decreasing the module voltage
down to 600V, additional points of operation can be operated in resonance, and
the remaining are closer to resonance. The option to decrease the module voltage
down to 600V, increases the number of required modules per arm from 12 to 15,
which requires to balance the losses of the LLCs and the grid-side stages.
author:
- first_name: Roland
full_name: Unruh, Roland
id: '34289'
last_name: Unruh
- first_name: Frank
full_name: Schafmeister, Frank
id: '71291'
last_name: Schafmeister
- first_name: Joachim
full_name: Böcker, Joachim
id: '66'
last_name: Böcker
orcid: 0000-0002-8480-7295
citation:
ama: 'Unruh R, Schafmeister F, Böcker J. Evaluation of MMCs for High-Power Low-Voltage
DC-Applications in Combination with the Module LLC-Design. In: 2020 22nd European
Conference on Power Electronics and Applications (EPE’20 ECCE Europe). IEEE;
2020. doi:10.23919/epe20ecceeurope43536.2020.9215687'
apa: Unruh, R., Schafmeister, F., & Böcker, J. (2020). Evaluation of MMCs for
High-Power Low-Voltage DC-Applications in Combination with the Module LLC-Design.
2020 22nd European Conference on Power Electronics and Applications (EPE’20
ECCE Europe). 22nd European Conference on Power Electronics and Applications
(EPE’20 ECCE Europe), Lyon, France. https://doi.org/10.23919/epe20ecceeurope43536.2020.9215687
bibtex: '@inproceedings{Unruh_Schafmeister_Böcker_2020, title={Evaluation of MMCs
for High-Power Low-Voltage DC-Applications in Combination with the Module LLC-Design},
DOI={10.23919/epe20ecceeurope43536.2020.9215687},
booktitle={2020 22nd European Conference on Power Electronics and Applications
(EPE’20 ECCE Europe)}, publisher={IEEE}, author={Unruh, Roland and Schafmeister,
Frank and Böcker, Joachim}, year={2020} }'
chicago: Unruh, Roland, Frank Schafmeister, and Joachim Böcker. “Evaluation of MMCs
for High-Power Low-Voltage DC-Applications in Combination with the Module LLC-Design.”
In 2020 22nd European Conference on Power Electronics and Applications (EPE’20
ECCE Europe). IEEE, 2020. https://doi.org/10.23919/epe20ecceeurope43536.2020.9215687.
ieee: 'R. Unruh, F. Schafmeister, and J. Böcker, “Evaluation of MMCs for High-Power
Low-Voltage DC-Applications in Combination with the Module LLC-Design,” presented
at the 22nd European Conference on Power Electronics and Applications (EPE’20
ECCE Europe), Lyon, France, 2020, doi: 10.23919/epe20ecceeurope43536.2020.9215687.'
mla: Unruh, Roland, et al. “Evaluation of MMCs for High-Power Low-Voltage DC-Applications
in Combination with the Module LLC-Design.” 2020 22nd European Conference on
Power Electronics and Applications (EPE’20 ECCE Europe), IEEE, 2020, doi:10.23919/epe20ecceeurope43536.2020.9215687.
short: 'R. Unruh, F. Schafmeister, J. Böcker, in: 2020 22nd European Conference
on Power Electronics and Applications (EPE’20 ECCE Europe), IEEE, 2020.'
conference:
end_date: 2020-09-11
location: Lyon, France
name: 22nd European Conference on Power Electronics and Applications (EPE'20 ECCE
Europe)
start_date: 2020-09-07
date_created: 2022-02-21T16:33:14Z
date_updated: 2022-02-21T17:00:16Z
department:
- _id: '52'
doi: 10.23919/epe20ecceeurope43536.2020.9215687
keyword:
- Multilevel converters
- Resonant converter
- High voltage power converters
- ZVS Converters
- Combination MMC LLC
language:
- iso: eng
main_file_link:
- url: https://ieeexplore.ieee.org/abstract/document/9215687
publication: 2020 22nd European Conference on Power Electronics and Applications (EPE'20
ECCE Europe)
publication_status: published
publisher: IEEE
status: public
title: Evaluation of MMCs for High-Power Low-Voltage DC-Applications in Combination
with the Module LLC-Design
type: conference
user_id: '34289'
year: '2020'
...