Please use this identifier to cite or link to this item:
|Title:||Self-learning neurofuzzy control of a liquid helium cryostat||Authors:||Tan, W.W.
|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|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.