Real-time control of a Tokamak plasma using neural networks


This paper presents results from the first use of neural networks for the real-time feedback control of high temperature plasmas in a Tokamak fusion experiment. The Tokamak is currently the principal experimental device for research into the magnetic confinement approach to controlled fusion. In the Tokamak, hydrogen plasmas, at temperatures of up to 100 Million K, are confined by strong magnetic fields. Accurate control of the position and shape of the plasma boundary requires real-time feedback control of the magnetic field structure on a time-scale of a few tens of microseconds. Software simulations have demonstrated that a neural network approach can give significantly better performance than the linear technique currently used on most Tokamak experiments. The practical application of the neural network approach requires high-speed hardware, for which a fully parallel implementation of the multi-layer perceptron, using a hybrid of digital and analogue technology, has been developed.

Divisions: College of Health & Life Sciences > School of Optometry > Optometry
Aston University (General)
Additional Information: Copyright of the Massachusetts Institute of Technology Press (MIT Press)
Event Title: Advances in Neural Information Processing Systems 1994
Event Type: Other
Event Dates: 1994-11-16 - 1994-11-18
Uncontrolled Keywords: neural networks,temperature plasmas,Tokamak,fusion,magnetic,magnetic fields
ISBN: 0262201046
Last Modified: 27 Dec 2023 09:54
Date Deposited: 13 Jul 2009 11:41
PURE Output Type: Chapter
Published Date: 1994-12-28
Authors: Bishop, Christopher M.
Haynes, P. S.
Smith, M. E. U.
Todd, T. N.
Trotman, D. L.
Windsor, C. G.



Version: Published Version

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