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Cloud-Based Model Predictive Control with Variable Horizon

Skarin, Per LU orcid ; Eker, Johan LU orcid and Årzén, Karl-Erik LU orcid (2020) 21st IFAC World Congress
Abstract
A novel method using the cloud to implement a variable horizon model predictive controller is presented. In case of sudden long delays and downtime, a graceful degradation is used. Robust, best effort strategies allow industrial grade use of the powerful, efficient, and quickly improving cloud ecosystems. The variable horizon strategy finds use in, for example, non-linear control problems, and the proposed method can be generalized to implement robust and scalable controllers that benefit from cloud technology. We show results from two horizon selection strategies, service degradation and connectivity issues.
Please use this url to cite or link to this publication:
author
; and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
host publication
International Federation of Automatic Control World Congress 2020
conference name
21st IFAC World Congress
conference location
Berlin, Germany
conference dates
2020-07-13 - 2020-07-17
external identifiers
  • scopus:85099883866
project
Control over the Cloud - Offloading, Elastic Computing, and Predictive Control
Nordic University Hub on Internet of Things
WASP: Autonomous Cloud
Mission-Critical Control over the Cloud
language
English
LU publication?
yes
id
017d1920-27bd-4fba-869a-6456937c8d76
date added to LUP
2020-08-21 09:46:00
date last changed
2023-11-20 09:29:42
@inproceedings{017d1920-27bd-4fba-869a-6456937c8d76,
  abstract     = {{A novel method using the cloud to implement a variable horizon model predictive controller is presented. In case of sudden long delays and downtime, a graceful degradation is used. Robust, best effort strategies allow industrial grade use of the powerful, efficient, and quickly improving cloud ecosystems. The variable horizon strategy finds use in, for example, non-linear control problems, and the proposed method can be generalized to implement robust and scalable controllers that benefit from cloud technology. We show results from two horizon selection strategies, service degradation and connectivity issues.}},
  author       = {{Skarin, Per and Eker, Johan and Årzén, Karl-Erik}},
  booktitle    = {{International Federation of Automatic Control World Congress 2020}},
  language     = {{eng}},
  month        = {{07}},
  title        = {{Cloud-Based Model Predictive Control with Variable Horizon}},
  url          = {{https://lup.lub.lu.se/search/files/88000580/SkarinIFAC2020.pdf}},
  year         = {{2020}},
}