DocumentCode :
768022
Title :
Temperature regulation with neural networks and alternative control schemes
Author :
Khalid, Marzuki ; Omatu, Sigeru ; Yusof, Rubiyah
Author_Institution :
Dept. of Inf. Sci. & Intelligent Syst., Tokushima Univ., Japan
Volume :
6
Issue :
3
fYear :
1995
fDate :
5/1/1995 12:00:00 AM
Firstpage :
572
Lastpage :
582
Abstract :
In this article, we compare the neuro-control algorithm to three other control algorithms: fuzzy logic control, generalized predictive control, and proportional-plus-integral control. Each of these four algorithms is implemented on a water bath temperature control system. The four systems are compared through experimental studies under identical conditions with respect to set-point regulation, the effect of unknown load disturbances, large parameter variation, and variable deadtime in the system. It is found that the neurocontrol system compares well with the other three control systems and offers encouraging advantages. From the results of the experimental studies, however, the best characteristics of each of these different classes of control systems may be combined for realizing a more efficient and intelligent control scheme
Keywords :
fuzzy control; intelligent control; neurocontrollers; predictive control; temperature control; deadtime; intelligent control; load disturbances; neural networks; neurocontrol system; set-point regulation; water bath temperature control; Adaptive control; Artificial neural networks; Automatic control; Control systems; Fuzzy logic; Fuzzy systems; Neural networks; Programmable control; Proportional control; Temperature control;
fLanguage :
English
Journal_Title :
Neural Networks, IEEE Transactions on
Publisher :
ieee
ISSN :
1045-9227
Type :
jour
DOI :
10.1109/72.377964
Filename :
377964
Link To Document :
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