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research article

Robust Resource-Aware Self-Triggered Model Predictive Control

Lian, Yingzhao  
•
Jiang, Yuning  
•
Stricker, Naomi
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January 1, 2022
Ieee Control Systems Letters

The wide adoption of wireless devices in the Internet of Things requires controllers that are able to operate with limited resources, such as battery life. Operating these devices robustly in an uncertain environment, while managing available resources, increases the difficultly of controller design. This letter proposes a robust self-triggered model predictive control approach to optimize a control objective while managing resource consumption. In particular, a novel zero-order-hold aperiodic discrete-time feedback control law is developed to ensure robust constraint satisfaction for continuous-time linear systems.

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Type
research article
DOI
10.1109/LCSYS.2021.3132654
Web of Science ID

WOS:000730527300003

Author(s)
Lian, Yingzhao  
Jiang, Yuning  
Stricker, Naomi
Thiele, Lothar
Jones, Colin N.
Date Issued

2022-01-01

Published in
Ieee Control Systems Letters
Volume

6

Start page

1724

End page

1729

Subjects

Automation & Control Systems

•

feedback control

•

ellipsoids

•

dynamic scheduling

•

batteries

•

predictive control

•

uncertainty

•

internet of things

•

robust optimal control

•

self-triggered model predictive control

•

constrained linear-systems

•

mpc

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LA  
Available on Infoscience
January 31, 2022
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/184889
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