제어로봇시스템학회:학술대회논문집

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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Temperature control of electric furnace using fuzzy rules and neural net

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  • Moon, Seok-Woo (Dept. of Electrical Engineering Inha University) ;
  • Kang, Min-Goo (Dept. of Electrical Engineering Inha University) ;
  • Lee, Jong-Ho (Dept. of Electrical Engineering Inha University) ;
  • Huh, Uk-Youl (Dept. of Electrical Engineering Inha University) ;
  • Lee, bong-Kuk (Dept. of Electrical Engineering Inha University)
  • 문석우 (인하대학교 공과대학 전기공학과) ;
  • 강민구 (인하대학교 공과대학 전기공학과) ;
  • 이종호 (인하대학교 공과대학 전기공학과) ;
  • 허욱열 (인하대학교 공과대학 전기공학과) ;
  • 이봉국 (인하대학교 공과대학 전기공학과)
  • Published : 1991.10.01
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Abstract

This paper presents the composite control method using fuzzy and neural network theory. Fuzzy theory is applied to make control rules and neural net is used to learn them and to generate proper control signals. The electric furnace is controlled to maintain the desired temperature and to minimize the fluctuation of the temperatures in various locations inside the furnace. This controller consists of three neural nets which deal with the average of the temperatures, variances of them and the temperature stabilizing mechanism. Experiments are performed with the target temperatures of 70.deg. C and 80.deg. C. Test results show that this simple method is very effective.

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