Transactions on Control, Automation and Systems Engineering

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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Design of Fuzzy-Sliding Model Control with the Self Tuning Fuzzy Inference Based on Genetic Algorithm and Its Application

  • Go, Seok-Jo (Department of Machine System, Dongeui Institute of Technology) ;
  • Lee, Min-Cheol (School of Mechanical Engineering, Pusan National University) ;
  • Park, Min-Kyn (Graduate school of Department of Mechanical and Intelligent Systems Engineering, Pusan National University)
  • Published : 2001.03.01
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Abstract

This paper proposes a self tuning fuzzy inference method by the genetic algorithm in the fuzzy-sliding mode control for a robot. Using this method, the number of inference rules and the shape of membership functions are optimized without an expert in robotics. The fuzzy outputs of the consequent part are updated by the gradient descent method. And, it is guaranteed that he selected solution become the global optimal solution by optimizing the Akaikes information criterion expressing the quality of the inference rules. The trajectory tracking simulation and experiment of the polishing robot show that the optimal fuzzy inference rules are automatically selected by the genetic algorithm and the proposed fuzzy-sliding mode controller provides reliable tracking performance during the polishing process.

Keywords

References

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