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http://dx.doi.org/10.5391/JKIIS.2012.22.2.239

Design of PID Controller for Magnetic Levitation RGV Using Genetic Algorithm Based on Clonal Selection  

Cho, Jae-Hoon (한경대학교 스마트물류기술연구센터)
Kim, Yong-Tae (한경대학교 스마트물류기술연구센터)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.22, no.2, 2012 , pp. 239-245 More about this Journal
Abstract
This paper proposes a novel optimum design method for the PID controller of magnetic levitation-based Rail-Guided Vehicle(RGV) by a genetic algorithm using clone selection method and a new performance index function with performances of both time and frequency domain. Generally, since an attraction type levitation system is intrinsically unstable and requires a delicate controller that is designed considering overshoot and settling time, it is difficult to completely satisfy the desired performance through the methods designed by conventional performance indexes. In the paper, the conventional performance indexes are analyzed and then a new performance index for Maglev-based RGV is proposed. Also, an advanced genetic algorithm which is designed using clonal selection algorithm for performance improvement is proposed. To verify the proposed algorithm and the performance index, we compare the proposed method with a simple genetic algorithm and particle swarm optimization. The simulation results show that the proposed method is more effective than conventional optimization methods.
Keywords
Maglev-based RGV; Genetic algorithm; PID controller; Clonal selection;
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