Cloud-Assisted Model Predictive Control

Per Skarin; Karl-Erik Årzén; Johan Eker; Maria Kihl

doi:10.1109/EDGE.2019.00033

Cloud-Assisted Model Predictive Control

Per Skarin, Karl-Erik Årzén, Johan Eker, Maria Kihl

Forskningsoutput: Kapitel i bok/rapport/Conference proceeding › Konferenspaper i proceeding › Peer review

Sammanfattning

In this paper we present a computational offloading
strategy with graceful degradation for executing Model Predictive
Control using the cloud. We show a method which allows for
seamless control assistance and design of flexible controllers using
the edge cloud. We examplify using a cyber-physical-system at
high frequency and illustrate how the system can be improved
while keeping the computational cost down.

Originalspråk	engelska
Titel på värdpublikation	2019 IEEE International Conference on Edge Computing
Undertitel på värdpublikation	(EDGE)
Förlag	IEEE - Institute of Electrical and Electronics Engineers Inc.
Sidor	110-112
Antal sidor	3
DOI	https://doi.org/10.1109/EDGE.2019.00033
Status	Published - 2019 aug. 26

Ämnesklassifikation (UKÄ)

Reglerteknik
Datorteknik
Kommunikationssystem
Robotteknik och automation

Fria nyckelord

cloud computing;control engineering computing;cyber-physical systems;predictive control;flexible controllers;edge cloud;cyber-physical-system;seamless control;cloud-assisted model predictive control;Cloud computing;Optimization;Delays;Data centers;Computational modeling;Mathematical model;Edge computing;Cloud, Edge, Time-sensitive, Mission-critical, Model Predictive Control, Control theory, Cyber-physical

Tillgång till dokument

10.1109/EDGE.2019.00033

http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8812219&isnumber=8812176

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Sec4Factory: Cybersäkerhet för nästa generations fabrik (SEC4FACTORY)
Gehrmann, C., Kihl, M., Hell, M., Fitzgerald, E., Toorani, M., Fitzgerald, E., Tärneberg, W. & Akbarian, F.
Stiftelsen för Strategisk Forskning, SSF
2018/04/01 → 2024/12/31
Projekt: Forskning
ELLIIT LU P01: 5G Wireless
Edfors, O.
Projekt: Forskning
E! Celtic-Plus 5G PERFECTA
Kihl, M., Fitzgerald, E. & Tärneberg, W.
Swedish Government Agency for Innovation Systems (Vinnova)
2018/08/27 → 2020/12/31
Projekt: Forskning

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title = "Cloud-Assisted Model Predictive Control",

abstract = "In this paper we present a computational offloading strategy with graceful degradation for executing Model Predictive Control using the cloud. We show a method which allows for seamless control assistance and design of flexible controllers using the edge cloud. We examplify using a cyber-physical-system at high frequency and illustrate how the system can be improved while keeping the computational cost down.",

keywords = "cloud computing;control engineering computing;cyber-physical systems;predictive control;flexible controllers;edge cloud;cyber-physical-system;seamless control;cloud-assisted model predictive control;Cloud computing;Optimization;Delays;Data centers;Computational modeling;Mathematical model;Edge computing;Cloud, Edge, Time-sensitive, Mission-critical, Model Predictive Control, Control theory, Cyber-physical",

author = "Per Skarin and Karl-Erik {\AA}rz{\'e}n and Johan Eker and Maria Kihl",

year = "2019",

month = aug,

day = "26",

doi = "10.1109/EDGE.2019.00033",

language = "English",

pages = "110--112",

booktitle = "2019 IEEE International Conference on Edge Computing",

publisher = "IEEE - Institute of Electrical and Electronics Engineers Inc.",

address = "United States",

}

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AU - Skarin, Per

AU - Årzén, Karl-Erik

AU - Eker, Johan

AU - Kihl, Maria

PY - 2019/8/26

Y1 - 2019/8/26

N2 - In this paper we present a computational offloading strategy with graceful degradation for executing Model Predictive Control using the cloud. We show a method which allows for seamless control assistance and design of flexible controllers using the edge cloud. We examplify using a cyber-physical-system at high frequency and illustrate how the system can be improved while keeping the computational cost down.

AB - In this paper we present a computational offloading strategy with graceful degradation for executing Model Predictive Control using the cloud. We show a method which allows for seamless control assistance and design of flexible controllers using the edge cloud. We examplify using a cyber-physical-system at high frequency and illustrate how the system can be improved while keeping the computational cost down.

KW - cloud computing;control engineering computing;cyber-physical systems;predictive control;flexible controllers;edge cloud;cyber-physical-system;seamless control;cloud-assisted model predictive control;Cloud computing;Optimization;Delays;Data centers;Computa

U2 - 10.1109/EDGE.2019.00033

DO - 10.1109/EDGE.2019.00033

M3 - Paper in conference proceeding

SP - 110

EP - 112

BT - 2019 IEEE International Conference on Edge Computing

PB - IEEE - Institute of Electrical and Electronics Engineers Inc.

ER -

Cloud-Assisted Model Predictive Control

Sammanfattning

Ämnesklassifikation (UKÄ)

Fria nyckelord

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Fingeravtryck

Projekt

Sec4Factory: Cybersäkerhet för nästa generations fabrik (SEC4FACTORY)

ELLIIT LU P01: 5G Wireless

E! Celtic-Plus 5G PERFECTA

Citera det här