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  4. Hierarchical Model Predictive Control in Fusion Reactors
 
conference paper

Hierarchical Model Predictive Control in Fusion Reactors

Garrido, I.
•
Coda, S.
•
Le, H. B.
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2016
2016 World Automation Congress (Wac)
World Automation Congress (WAC)

Nuclear fusion still has to pass several milestones on its way to successful energy production, one of them being successful plasma stabilization. The present article presents an innovative control implementation related to plasma control for the generation of electricity with magnetically confined plasma. The implementation has been carried out over a specific device of tokamak type, called Tokamak it Configuration Variable (TCV). This novel hybrid control design allows for real time implementation of an optimal model predictive control over a large scale complex system with small time constant. At each closed loop iteration, the full model is first controlled by a straightforward controller, then the output values are used for model reduction so that finally the discretized control system is optimized only for the variables of interest. In the case of the TCV, this novel hybrid model predictive control enhances the power availability on the actuators and extends the pulse duration. Thus, this control strategy will help to achieve fusion energy stated goal of "ignition", where nuclear fusion generates as much energy as it is needed to start the reaction.

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Type
conference paper
DOI
10.1109/WAC.2016.7583003
Web of Science ID

WOS:000386618400059

Author(s)
Garrido, I.
Coda, S.
Le, H. B.
Moret, J. M.
Queral, V.
Sevillano, G.
Garrido, A. J.
Date Issued

2016

Publisher

Ieee

Publisher place

New York

Published in
2016 World Automation Congress (Wac)
Total of pages

6

Series title/Series vol.

World Automation Congress

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
SPC  
Event nameEvent placeEvent date
World Automation Congress (WAC)

PR

JUL 31-AUG 04, 2016

Available on Infoscience
January 24, 2017
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/133392
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