Self-learning neurofuzzy control of a liquid helium cryostat

13Citations
Citations of this article
4Readers
Mendeley users who have this article in their library.
Get full text

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.

Cite

CITATION STYLE

APA

Tan, W. W., & Dexter, A. L. (1999). Self-learning neurofuzzy control of a liquid helium cryostat. Control Engineering Practice, 7(10), 1209–1220. https://doi.org/10.1016/S0967-0661(99)00096-9

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free