Comparison of DC motor position control simulation using MABSA-FLC and PSO-FLC
This paper explained about the standard fuzzy logic controller that will be compared in terms of performance for simulation with a modified adaptive bats sonar algorithm (MABSA) and also a particle swarm optimization (PSO) algorithm. A MATLAB toolbox is used to design the fuzzy logic controller (FLC...
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Main Authors: | , |
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Format: | Conference or Workshop Item |
Language: | English |
Published: |
Institute of Electrical and Electronics Engineers Inc.
2019
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Subjects: | |
Online Access: | http://umpir.ump.edu.my/id/eprint/25145/1/Norainaa%20Paper%201.pdf http://umpir.ump.edu.my/id/eprint/25145/ http://doi.org/10.1109/CSPA.2019.8696032 |
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Summary: | This paper explained about the standard fuzzy logic controller that will be compared in terms of performance for simulation with a modified adaptive bats sonar algorithm (MABSA) and also a particle swarm optimization (PSO) algorithm. A MATLAB toolbox is used to design the fuzzy logic controller (FLC). The DC motor was modeled, converted to a subsystem in Simulink and then the MATLAB toolbox is used to design the FLC. The methodology composed of the designing and also the simulation of DC motor with a fuzzy logic controller and optimization of the difference algorithm will be used as a benchmark for the performance of the fuzzy system. The results obtained from the Simulink scope are compared with the different algorithm used for the dynamic response of the closed-loop system and also the system with and without a controller will be compared. Parameters such as the rise and settling time in seconds and maximum overshoot in percent will be part of the simulation result. The overall performance shows that a system with MABSA-FLC performs well compared to the system with FLC and PSO-FLC. |
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