제어로봇시스템학회:학술대회논문집

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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Design & application of adaptive fuzzy-neuro controllers

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  • Kang, Kyeng-Wuon (Dept. of Electronics Engineering, Chung Ang University) ;
  • Kim, Yong-Min (Dept. of Electronics Engineering, Chung Ang University) ;
  • Kang, Hoon (Dept. of Control & Instrumentation Engineering, Chung Ang University) ;
  • Jeon, Hong-Tae (Dept. of Electronics Engineering, Chung Ang University)
  • 강경운 (중앙대학교 전자공학과) ;
  • 김용민 (중앙대학교 전자공학과) ;
  • 강훈 (중앙대학교 제어계측공학과) ;
  • 전홍태 (중앙대학교 전자공학과)
  • Published : 1993.10.01
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Abstract

In this paper, we focus upon the design and applications of adaptive fuzzy-neuro controllers. An intelligent control system is proposed by exploiting the merits of two paradigms, a fuzzy logic controller and a neural network, assuming that we can modify in real time the consequential parts of the rulebase with adaptive learning, and that initial fuzzy control rules are established in a temporarily stable region. We choose the structure of fuzzy hypercubes for the fuzzy controller, and utilize the Perceptron learning rule in order to update the fuzzy control rules on-line with the output error. And, the effectiveness and the robustness of this intelligent controller are shown with application of the proposed adaptive fuzzy-neuro controller to control of the cart-pole system.

Keywords