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http://dx.doi.org/10.5370/KIEE.2017.66.4.701

Design of TLBO-based Optimal Fuzzy PID Controller for Magnetic Levitation System  

Cho, Jae-Hoon (Smart Logistics Technology Institute, Hankyong National University)
Kim, Yong Tae (Department of Electrical, Electronic and Control Engineering, Hankyong National University)
Publication Information
The Transactions of The Korean Institute of Electrical Engineers / v.66, no.4, 2017 , pp. 701-708 More about this Journal
Abstract
This paper proposes an optimum design method using Teaching-Learning-based optimization for the fuzzy PID controller of Magnetic levitation rail-guided vehicle. Since an attraction-type levitation system is intrinsically unstable, it is difficult to completely satisfy the desired performance through the conventional control methods. In the paper, a fuzzy PID controller with fixed parameters is applied and then the optimum parameters of fuzzy PID controller are selected by Teaching-Learning optimization. For the fitness function of Teaching-Learning optimization, the performance index of PID controller is used. To verify the performances of the proposed method, we use a Maglev model and compare the proposed method with the performance of PID controller. The simulation results show that the proposed method is more effective than conventional PID controller.
Keywords
Teaching-learning-based optimization; Fuzzy PID controller; Magnetic levitation; Rail-guided vehicle;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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