Proceedings of the Korean Institute of Intelligent Systems Conference (한국지능시스템학회:학술대회논문집)

Korean Institute of Intelligent Systems (한국지능시스템학회)
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RULE-BASE SIZE-REDUCTION TECHNIQUES IN A LEARNING FUZZY CONTROLLER

  • Lembessis, E. (AMBER S. A. Computer System, The“Heracles Group”) ;
  • Tnascheit, R. (Department of Electrical Engineering, PUC-Rio)
  • Published : 1993.06.01
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Abstract

In this paper we consider techniques for reducing the generated number of rules in learning fuzzy controllers of the state-space action-reinforcement type that can be simply implemented and that behave well in the presence of process noise. Fewer rules lead to better performance, less contradiction in controller action estimation, smaller required execution-time and make it easier for a human to comprehend the generated rules and possibly intervene.

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