Cloud-Assisted Model Predictive Control
Skarin, Per LU
; Årzén, Karl-Erik
LU
; Eker, Johan
LU
and Kihl, Maria
LU
(2019)
p.110-112
- 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.
- Abstract (Swedish)
- 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.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/d979cbba-527c-45e4-87d1-e1cdbf5ab5bc
- author
- Skarin, Per
LU
; Årzén, Karl-Erik
LU
; Eker, Johan
LU
and Kihl, Maria
LU
- organization
- publishing date
- 2019-08-26
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- 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
- host publication
- 2019 IEEE International Conference on Edge Computing : (EDGE) - (EDGE)
- pages
- 3 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- external identifiers
-
- scopus:85072531793
- DOI
- 10.1109/EDGE.2019.00033
- project
- Control over the Cloud - Offloading, Elastic Computing, and Predictive Control
- Mission-Critical Control over the Cloud
- Cyber Security for Next Generation Factory (SEC4FACTORY)
- E! Celtic-Plus 5G PERFECTA
- WASP: Autonomous Cloud
- ELLIIT LU P01: 5G Wireless
- language
- English
- LU publication?
- yes
- id
- d979cbba-527c-45e4-87d1-e1cdbf5ab5bc
- alternative location
- http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8812219&isnumber=8812176
- date added to LUP
- 2019-11-12 13:32:38
- date last changed
- 2025-10-14 12:11:58
@inproceedings{d979cbba-527c-45e4-87d1-e1cdbf5ab5bc,
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.}},
author = {{Skarin, Per and Årzén, Karl-Erik and Eker, Johan and Kihl, Maria}},
booktitle = {{2019 IEEE International Conference on Edge Computing : (EDGE)}},
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}},
language = {{eng}},
month = {{08}},
pages = {{110--112}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
title = {{Cloud-Assisted Model Predictive Control}},
url = {{http://dx.doi.org/10.1109/EDGE.2019.00033}},
doi = {{10.1109/EDGE.2019.00033}},
year = {{2019}},
}