Real Time Hybrid Model Predictive Control for the Current Profile of the Tokamak à Configuration Variable (TCV)
1
Faculty of Engineering, University of the Basque Country (UPV/EHU), Paseo Rafael Moreno 3, Bilbao 48013, Spain
2
Centre de Recherches en Physique des Plasmas, École Polytechnique Fédérale de Lausanne (CRPP-EPFL), CH-1015 Lausanne, Switzerland
*
Author to whom correspondence should be addressed.
Academic Editor: Matthew Hole
Energies 2016, 9(8), 609; https://doi.org/10.3390/en9080609
Received: 27 February 2016 / Revised: 26 July 2016 / Accepted: 27 July 2016 / Published: 3 August 2016
(This article belongs to the Special Issue Fusion Power)
Plasma stability is one of the obstacles in the path to the successful operation of fusion devices. Numerical control-oriented codes as it is the case of the widely accepted RZIp may be used within Tokamak simulations. The novelty of this article relies in the hierarchical development of a dynamic control loop. It is based on a current profile Model Predictive Control (MPC) algorithm within a multiloop structure, where a MPC is developed at each step so as to improve the Proportional Integral Derivative (PID) global scheme. The inner control loop is composed of a PID-based controller that acts over the Multiple Input Multiple Output (MIMO) system resulting from the RZIp plasma model of the Tokamak à Configuration Variable (TCV). The coefficients of this PID controller are initially tuned using an eigenmode reduction over the passive structure model. The control action corresponding to the state of interest is then optimized in the outer MPC loop. For the sake of comparison, both the traditionally used PID global controller as well as the multiloop enhanced MPC are applied to the same TCV shot. The results show that the proposed control algorithm presents a superior performance over the conventional PID algorithm in terms of convergence. Furthermore, this enhanced MPC algorithm contributes to extend the discharge length and to overcome the limited power availability restrictions that hinder the performance of advanced tokamaks.
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MDPI and ACS Style
Garrido, I.; Garrido, A.J.; Coda, S.; Le, H.B.; Moret, J.M. Real Time Hybrid Model Predictive Control for the Current Profile of the Tokamak à Configuration Variable (TCV). Energies 2016, 9, 609. https://doi.org/10.3390/en9080609
AMA Style
Garrido I, Garrido AJ, Coda S, Le HB, Moret JM. Real Time Hybrid Model Predictive Control for the Current Profile of the Tokamak à Configuration Variable (TCV). Energies. 2016; 9(8):609. https://doi.org/10.3390/en9080609
Chicago/Turabian StyleGarrido, Izaskun; Garrido, Aitor J.; Coda, Stefano; Le, Hoang B.; Moret, Jean M. 2016. "Real Time Hybrid Model Predictive Control for the Current Profile of the Tokamak à Configuration Variable (TCV)" Energies 9, no. 8: 609. https://doi.org/10.3390/en9080609
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