Tuning of FOPID controller for robotic manipulator using genetic and multiple-objective genetic algorithms
This study compares the performances of the GA-FOPID and MOGA-FOPID controllers, which are Fractional Order Proportional-Integral-Derivative (FOPID) controllers tuned using genetic algorithm and multiple-objective genetic algorithm for position tracking accuracy of robotic manipulator, respectively....
| Main Authors: | , , , , , , |
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| Format: | Conference or Workshop Item |
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Springer
2023
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| _version_ | 1825939623493238784 |
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| author | Hambali, Nurul Faqihah Norsahperi, Nor Mohd Haziq Mohd Hisban, Mas Athirah Hassan, Mohd Khair Wan Hasan, Wan Zuha Ismail, Luthffi Idzhar Ramli, Hafiz Rashidi |
| author_facet | Hambali, Nurul Faqihah Norsahperi, Nor Mohd Haziq Mohd Hisban, Mas Athirah Hassan, Mohd Khair Wan Hasan, Wan Zuha Ismail, Luthffi Idzhar Ramli, Hafiz Rashidi |
| author_sort | Hambali, Nurul Faqihah |
| collection | UPM |
| description | This study compares the performances of the GA-FOPID and MOGA-FOPID controllers, which are Fractional Order Proportional-Integral-Derivative (FOPID) controllers tuned using genetic algorithm and multiple-objective genetic algorithm for position tracking accuracy of robotic manipulator, respectively. The tuning process of six control gains in the three FOPID controllers is technically challenging to achieve high position accuracy of robotic manipulator. This study is performed to objectively assess the performances of genetic algorithm and multiple-objective genetic algorithm in tuning the six control gains in the FOPID controller. From the simulation study, it is interesting to note that the GA-FOPID and MOGA-FOPID controllers produce approximately 4.18 and 4.37 reductions of the mean square error in the angular position accuracy response of robotic manipulator as compared with the GA-PID controller. It is envisaged that the GA-FOPID and MOGA-FOPID controllers can be useful in designing effective position tracking accuracy of robotic manipulators. |
| first_indexed | 2024-12-09T02:20:19Z |
| format | Conference or Workshop Item |
| id | upm.eprints-108366 |
| institution | Universiti Putra Malaysia |
| last_indexed | 2024-12-09T02:20:19Z |
| publishDate | 2023 |
| publisher | Springer |
| record_format | dspace |
| spelling | upm.eprints-1083662024-11-18T07:57:51Z http://psasir.upm.edu.my/id/eprint/108366/ Tuning of FOPID controller for robotic manipulator using genetic and multiple-objective genetic algorithms Hambali, Nurul Faqihah Norsahperi, Nor Mohd Haziq Mohd Hisban, Mas Athirah Hassan, Mohd Khair Wan Hasan, Wan Zuha Ismail, Luthffi Idzhar Ramli, Hafiz Rashidi This study compares the performances of the GA-FOPID and MOGA-FOPID controllers, which are Fractional Order Proportional-Integral-Derivative (FOPID) controllers tuned using genetic algorithm and multiple-objective genetic algorithm for position tracking accuracy of robotic manipulator, respectively. The tuning process of six control gains in the three FOPID controllers is technically challenging to achieve high position accuracy of robotic manipulator. This study is performed to objectively assess the performances of genetic algorithm and multiple-objective genetic algorithm in tuning the six control gains in the FOPID controller. From the simulation study, it is interesting to note that the GA-FOPID and MOGA-FOPID controllers produce approximately 4.18 and 4.37 reductions of the mean square error in the angular position accuracy response of robotic manipulator as compared with the GA-PID controller. It is envisaged that the GA-FOPID and MOGA-FOPID controllers can be useful in designing effective position tracking accuracy of robotic manipulators. Springer 2023 Conference or Workshop Item PeerReviewed Hambali, Nurul Faqihah and Norsahperi, Nor Mohd Haziq and Mohd Hisban, Mas Athirah and Hassan, Mohd Khair and Wan Hasan, Wan Zuha and Ismail, Luthffi Idzhar and Ramli, Hafiz Rashidi (2023) Tuning of FOPID controller for robotic manipulator using genetic and multiple-objective genetic algorithms. In: Intelligent Manufacturing and Mechatronics. iM3F 2023, 7-8 August 2023, Pekan, Malaysia. (pp. 1-9). https://link.springer.com/chapter/10.1007/978-981-99-8819-8_47 10.1007/978-981-99-8819-8_47 |
| spellingShingle | Hambali, Nurul Faqihah Norsahperi, Nor Mohd Haziq Mohd Hisban, Mas Athirah Hassan, Mohd Khair Wan Hasan, Wan Zuha Ismail, Luthffi Idzhar Ramli, Hafiz Rashidi Tuning of FOPID controller for robotic manipulator using genetic and multiple-objective genetic algorithms |
| title | Tuning of FOPID controller for robotic manipulator using genetic and multiple-objective genetic algorithms |
| title_full | Tuning of FOPID controller for robotic manipulator using genetic and multiple-objective genetic algorithms |
| title_fullStr | Tuning of FOPID controller for robotic manipulator using genetic and multiple-objective genetic algorithms |
| title_full_unstemmed | Tuning of FOPID controller for robotic manipulator using genetic and multiple-objective genetic algorithms |
| title_short | Tuning of FOPID controller for robotic manipulator using genetic and multiple-objective genetic algorithms |
| title_sort | tuning of fopid controller for robotic manipulator using genetic and multiple objective genetic algorithms |
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