Design of PSO-based Fuzzy Logic Controller for single Axis Magnetic Levitation System.
In this paper, a particle swarm optimization (PSO) method is proposed to design an optimal robust fuzzy logic controller (FLC). The objective of this paper is to design a nonlinear optimal robust controller for the single axis magnetic levitation system with high accuracy. PSO algorithm is applied t...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
2011
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| Online Access: | http://psasir.upm.edu.my/id/eprint/23430/ |
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| Institution: | Universiti Putra Malaysia |
| Language: | English |
| Summary: | In this paper, a particle swarm optimization (PSO) method is proposed to design an optimal robust fuzzy logic controller (FLC). The objective of this paper is to design a nonlinear optimal robust controller for the single axis magnetic levitation system with high accuracy. PSO algorithm is applied to search globally optimal parameters of FLCs. Three different FLCs are designed. First, proportional derivative (PD)-like FLC. Second, the FLC is based on the PSO algorithm to find the optimal range of the eight linguistic membership functions (FLC1 with PSO algorithm). Finally, the FLC is based on the PSO algorithm to find the optimal range and shape of the four linguistic membership functions (FLC2 with PSO algorithm). The performances of three different FLCs are compared. Simulation results show that PSO-based optimal FLCs find the optimal range and shape of the four linguistic membership functions and achieved better performance than the other proposed controllers, minimizing 48 fuzzy rules. © 2011 Institute of Electrical Engineers of Japan. |
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