Simulation Study on Self-learning Fuzzy Control of CO Concentration

  • Tanaka, Kazuo (Department of Mechanical Systems Engineering Kanazawa University) ;
  • Sano, Manabu (Department of Mechanical Systems Engineering Kanazawa University) ;
  • Watanabe, Hiroyuki (Department of Computer Science The University of North Carolina)
  • Published : 1993.06.01

Abstract

This paper presents a simulation study on two self-learning control systems for a fuzzy prediction model of CO (carbon monoxide) concentration:linear control and fuzzy control. The self-learning control systems are realized by using Widrow-Hoff learning rule which is a basic learning method in neural networks. Simulation results show that the learning efficiency of fuzzy controller is superior to that of linear controller.

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