Dynamic optimization of tokamak plasmas via control parameterization and the time-scaling transformation

Fusion nuclear reactions, in which multiple atomic nuclei collide to form a single atomic nucleus, can only occur at extremely high temperatures, where all matter is in the plasma state. In the majority of today's experimental fusion reactors, the fusion plasma is confined to a torus shape usin...

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Bibliographic Details
Published in2015 34th Chinese Control Conference (CCC) pp. 2428 - 2433
Main Authors Zhigang Ren, Chao Xu, Qun Lin, Loxton, Ryan
Format Conference Proceeding Journal Article
LanguageEnglish
Published Technical Committee on Control Theory, Chinese Association of Automation 01.07.2015
Subjects
Approximation
Approximation methods
Computer simulation
Control Parameterization
Current Profile Control
Dynamic Optimization
Finite element analysis
Finite Element Method
Mathematical models
Nuclear Fusion
Nuclei
Optimal control
Optimization
Parametrization
Partial differential equations
Plasmas
Time-scaling Transformation
Tokamak devices
Tokamaks
Online AccessGet full text
ISSN1934-1768
DOI10.1109/ChiCC.2015.7260014

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Summary:Fusion nuclear reactions, in which multiple atomic nuclei collide to form a single atomic nucleus, can only occur at extremely high temperatures, where all matter is in the plasma state. In the majority of today's experimental fusion reactors, the fusion plasma is confined to a torus shape using a magnetic confinement system called a tokamak. The performance of a tokamak depends crucially on the current spatial profile, which is related to the poloidal magnetic flux. Accordingly, in this paper, we investigate a finite-time optimal control problem in which the aim is to drive the current spatial profile to within close proximity of a desired target profile, subject to a parabolic PDE governing the evolution of the poloidal magnetic flux. To solve this optimal control problem, we first use the finite element method to approximate the PDE model by an ODE model. Then, we apply the control parameterization and time-scaling techniques to obtain an approximate finite-dimensional optimization problem, which can be solved using sequential quadratic programming methods. Simulation results using experimental data from the DIII-D tokamak in San Diego, California demonstrate the effectiveness of the proposed approach.
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ISSN:1934-1768
DOI:10.1109/ChiCC.2015.7260014