Experimental dataset to develop a parametric model based of DC geared motor in feeder machine
This paper presents the application of a System Identification based on Particle Swarm Optimization (PSO) technique to develop parametric model of experimental dataset of DC geared motor in feeder machine. The experiment was conducted to measure the input (voltage) and output (voltage) data. The act...
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| Main Authors: | , , , , |
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| Format: | Article |
| Published: |
Institute of Advanced Engineering and Science (IAES)
2019
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| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/3757/ http://doi.org/10.11591/ijece.v9i3.pp1576-1584 |
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| Summary: | This paper presents the application of a System Identification based on Particle Swarm Optimization (PSO) technique to develop parametric model of experimental dataset of DC geared motor in feeder machine. The experiment was conducted to measure the input (voltage) and output (voltage) data. The actual data is used to be optimized using PSO algorithm. The parameter emphasized is time, mean square error (mse) and average time. One of the best models has been chosen based on the optimum parameters. |
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