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International Journal of Control, Automation and Systems v.3 no.2, 2005년, pp.236 - 243   피인용횟수: 1

SA-selection-based Genetic Algorithm for the Design of Fuzzy Controller

Han Chang-Wook    (School of Electrical Engineering and Computer Science, Yeungnam University   ); Park Jung-Il    (School of Electrical Engineering and Computer Science, Yeungnam University  );
  • 초록

    This paper presents a new stochastic approach for solving combinatorial optimization problems by using a new selection method, i.e. SA-selection, in genetic algorithm (GA). This approach combines GA with simulated annealing (SA) to improve the performance of GA. GA and SA have complementary strengths and weaknesses. While GA explores the search space by means of population of search points, it suffers from poor convergence properties. SA, by contrast, has good convergence properties, but it cannot explore the search space by means of population. However, SA does employ a completely local selection strategy where the current candidate and the new modification are evaluated and compared. To verify the effectiveness of the proposed method, the optimization of a fuzzy controller for balancing an inverted pendulum on a cart is considered.


  • 주제어

    Combinatorial optimization problem .   fuzzy control .   genetic algorithm .   simulated annealing.  

  • 참고문헌 (15)

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  • 이 논문을 인용한 문헌 (1)

    1. Han, Chang-Wook 2013. "Optimization of Max-Plus based Neural Networks using Genetic Algorithms" 信號處理·시스템學會 論文誌 = Journal of the institute of signal processing and systems, 14(1): 57~61     

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