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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)
Publication Information
International Journal of Control, Automation, and Systems / v.3, no.2, 2005 , pp. 236-243 More about this Journal
Abstract
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.
Keywords
Combinatorial optimization problem; fuzzy control; genetic algorithm; simulated annealing;
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Times Cited By Web Of Science : 5  (Related Records In Web of Science)
Times Cited By SCOPUS : 5
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