Please use this identifier to cite or link to this item: https://doi.org/10.1016/S0967-0661(99)00096-9
Title: Self-learning neurofuzzy control of a liquid helium cryostat
Authors: Tan, W.W. 
Dexter, A.L.
Keywords: Adaptive neurofuzzy control on-line training
Issue Date: Oct-1999
Citation: Tan, W.W., Dexter, A.L. (1999-10). Self-learning neurofuzzy control of a liquid helium cryostat. Control Engineering Practice 7 (10) : 1209-1220. ScholarBank@NUS Repository. https://doi.org/10.1016/S0967-0661(99)00096-9
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.
Source Title: Control Engineering Practice
URI: http://scholarbank.nus.edu.sg/handle/10635/62745
ISSN: 09670661
DOI: 10.1016/S0967-0661(99)00096-9
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