Design and Implementation of Hybrid Fuzzy Control of a Magnetic Levitation System
In this research paper scientific model of the levitation system based on the magnetic field has been implemented with the help of the fuzzy-logic controller. The behaviour of alluring (maglev) mainly based on the PID-controller being used. Therefore, a controller based on PID has been organized to...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
The University of Lahore
2020-09-01
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| Series: | Pakistan Journal of Engineering & Technology |
| Subjects: | |
| Online Access: | http://dev.ojs.com/index.php/pakjet/article/view/427 |
| Summary: | In this research paper scientific model of the levitation system based on the magnetic field has been implemented with the help of the fuzzy-logic controller. The behaviour of alluring (maglev) mainly based on the PID-controller being used. Therefore, a controller based on PID has been organized to control efficiently and get the desired performance of the maglev system under study. But, as evident from the literature review, a PID controller has its limitations and is typically undefined in the situation of changing the load because PID controllers have fixed constraints. Due to these limitations, a controller that is based on fuzzy logic has been designed to overcome these problems. By using the fuzzy logic, again has been selected for the PID-controller by using the different values of load and set the reference value to calculate the gain error. Best suited membership functions have been used to fuzzifier the gain parameters. An optimal inference engine has been designed to map inputs to the corresponding outputs. Finally, a de-fuzzifier has been designed to get crisp values which reflect the gain constraints of the designed PID Regulator. This fuzzy controller supervises the conventional PID controller to automatically adjust its parameters to control the maglev system even with varying load and varying air gap changes. |
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| ISSN: | 2664-2042 2664-2050 |