Journal of the Institute of Convergence Signal Processing (융합신호처리학회논문지)

The Korea Institute of Convergence Signal Processing (한국융합신호처리학회)
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Design of Tree Architecture of Fuzzy Controller based on Genetic Optimization

  • Han, Chang-Wook (Dept. of Electrical Engineering, Dong-Eui University) ;
  • Oh, Se-Jin (Radio Astronomy Division, Korea Astronomy and Space Science Institute)
  • Received : 2010.06.16
  • Accepted : 2010.07.29
  • Published : 2010.07.30
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Abstract

As the number of input and fuzzy set of a fuzzy system increase, the size of the rule base increases exponentially and becomes unmanageable (curse of dimensionality). In this paper, tree architectures of fuzzy controller (TAFC) is proposed to overcome the curse of dimensionality problem occurring in the design of fuzzy controller. TAFC is constructed with the aid of AND and OR fuzzy neurons. TAFC can guarantee reduced size of rule base with reasonable performance. For the development of TAFC, genetic algorithm constructs the binary tree structure by optimally selecting the nodes and leaves, and then random signal-based learning further refines the binary connections (two-step optimization). An inverted pendulum system is considered to verify the effectiveness of the proposed method by simulation.

Keywords

References

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