A Neural Network Approach to Tokamak Equilibrium Control

  • Chris Bishop
  • Peter Cox
  • Paul Haynes
  • Colin Roach
  • Mike Smith
  • Tom Todd
  • David Trotman
Part of the Perspectives in Neural Computing book series (PERSPECT.NEURAL)

Abstract

We exploit the properties of the multilayer perceptron to develop a neural network approach to the feedback control of plasma position and shape in a tokamak experiment. The requirements of large bandwidth and high precision have led us to develop a custom hybrid analogue-digital hardware implementation of the neural network using conventional components. It is planned to demonstrate a complete system on the COMPASS tokamak at Culham Laboratory.

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References

  1. [1]
    Bishop C M, Strachan I G D, O’Rourke J, Maddison G P and Thomas P R (1992) Reconstruction of Tokamak Density Profiles using Feedforward Networks Neural Computing and Applications 1 No 1.Google Scholar
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    Braams B J, Jilge W and Lackner K (1986) Fast Determination of Plasma Parameters Through Function Parameterisation, Nuclear Fusion 26 No 6, 699.CrossRefGoogle Scholar
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    Hofmann F and Tonetti G (1988) Fast Identification of Plasma Boundary and X-Points in Elongated Tokamaks, Nuclear Fusion 28 No 3, 519.CrossRefGoogle Scholar
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    Lister J B and Schnurrenberger H (1991) Fast Non-Linear Extraction of Plasma Parameters Using a Neural Network Mapping, Nuclear Fusion 31 no 7, 1291.CrossRefGoogle Scholar
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    Osborne T H, Fukumoto H, Hosogane N et al (1986) Plasma Shape and Position Control on DIIID, Bull. Am. Phys. Soc. (1986) 31 No 9, 1502.Google Scholar

Copyright information

© Springer-Verlag London Limited 1992

Authors and Affiliations

  • Chris Bishop
    • 1
  • Peter Cox
    • 2
  • Paul Haynes
    • 2
  • Colin Roach
    • 2
  • Mike Smith
    • 2
  • Tom Todd
    • 2
  • David Trotman
    • 2
  1. 1.Harwell LaboratoryAEA TechnologyOxfordshireUK
  2. 2.Culham LaboratoryAEA TechnologyOxfordshireUK

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