Learning of a backpropagation neural network to tune a fuzzy control of a thermal system

Author

Urbieta Parrazales, R. ; Ramirez, Marco A. ; Osvaldo Espinosa, S. ; Elena Aguilar, J. ; De Luca, Adriano

Author_Institution

Centro de Investigacion en Comput., Mexico

fYear

2000

fDate

2000

Firstpage

182

Lastpage

184

Abstract

This regular paper describes three important aspects: design, simulation and implementation of neuro-fuzzy control applied to the temperature variable of a thermal system with a range of 25°C to 75°C and resolution of 0.01%. In the design were found the membership functions and the fuzzy rules base already optimized of the fuzzy controller by means of a backpropagation neural network trained to 120 learning cycles. The simulation presents basic tables of the fuzzy controller obtained by the neural network. The implementation of the program of the fuzzy controller was effected using a 486 PC with conversion card A/D and of 8-bit port output

Keywords

backpropagation; fuzzy control; neurocontrollers; process control; temperature control; 25 to 75 degC; backpropagation neural network; conversion card A/D; fuzzy rules base; learning cycles; membership functions; neuro-fuzzy control; process control; temperature variable; thermal system; Backpropagation; Digital relays; Error correction; Fuzzy control; Fuzzy logic; Neural networks; Temperature control; Temperature distribution; Temperature measurement; Temperature sensors;

fLanguage

English

Publisher

ieee

Conference_Titel

Mixed-Signal Design, 2000. SSMSD. 2000 Southwest Symposium on

Conference_Location

San Diego, CA

Print_ISBN

0-7803-5975-5

Type

conf

DOI

10.1109/SSMSD.2000.836470

Filename

836470