Self-learning neurofuzzy control of a liquid helium cryostat

  • Tan W
  • Dexter A
  • 3

    Readers

    Mendeley users who have this article in their library.
  • 13

    Citations

    Citations of this article.

Abstract

The paper demonstrates that a self-learning neurofuzzy controller is able to regulate the temperature in a liquid helium cryostat. In order to simplify the task of commissioning the controller, a strategy for choosing the user-selected parameters from an equivalent proportional-plus-integral controller (PI) is derived. Experimental results which illustrate the potential of the proposed control scheme are presented. The performance of the self-learning neurofuzzy controller is also compared with that of a commercial gain-scheduled PI controller.

Author-supplied keywords

  • Adaptive neurofuzzy control on-line training

Get free article suggestions today

Mendeley saves you time finding and organizing research

Sign up here
Already have an account ?Sign in

Find this document

Authors

  • W. W. Tan

  • A. L. Dexter

Cite this document

Choose a citation style from the tabs below

Save time finding and organizing research with Mendeley

Sign up for free