Induction motor control and speed estimation via adaptive and artificial intelligence method
This paper shows the optimization of the parameters of PI controllers in the application of vector control of a three-phase induction motor by genetic algorithm for the set optimality criterion. There is also the projecting procedure as well as the comparative analysis of the performances of speed e...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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National Society of Processing and Energy in Agriculture, Novi Sad
2011-01-01
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| Series: | Journal on Processing and Energy in Agriculture |
| Subjects: | |
| Online Access: | https://scindeks-clanci.ceon.rs/data/pdf/1821-4487/2011/1821-44871104251K.pdf |
| _version_ | 1811186819539140608 |
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| author | Kamenko Ilija Nikolić Perica Matić Dragan Bugarski Vladimir |
| author_facet | Kamenko Ilija Nikolić Perica Matić Dragan Bugarski Vladimir |
| author_sort | Kamenko Ilija |
| collection | DOAJ |
| description | This paper shows the optimization of the parameters of PI controllers in the application of vector control of a three-phase induction motor by genetic algorithm for the set optimality criterion. There is also the projecting procedure as well as the comparative analysis of the performances of speed estimator based on MRAS observer and speed estimator based on ANN. The basis of the research is a mathematical model of vector control of a three-phase induction motor, which was developed in MATLAB/Simulink. The experimental analysis of the results was carried on the laboratory model of electric motor drive based on the dSPACE card. The application of the encoder provides a smaller measurement error, whereas the application of estimators is possible in the cases for which pinpoint accuracy is not required and for which the price and/or reliability are of greater interest. |
| first_indexed | 2024-04-11T13:52:50Z |
| format | Article |
| id | doaj.art-76cfc8989d3b48e5acfcaf4b5839a9fc |
| institution | Directory Open Access Journal |
| issn | 1821-4487 2956-0195 |
| language | English |
| last_indexed | 2024-04-11T13:52:50Z |
| publishDate | 2011-01-01 |
| publisher | National Society of Processing and Energy in Agriculture, Novi Sad |
| record_format | Article |
| series | Journal on Processing and Energy in Agriculture |
| spelling | doaj.art-76cfc8989d3b48e5acfcaf4b5839a9fc2022-12-22T04:20:30ZengNational Society of Processing and Energy in Agriculture, Novi SadJournal on Processing and Energy in Agriculture1821-44872956-01952011-01-011542512541821-44871104251KInduction motor control and speed estimation via adaptive and artificial intelligence methodKamenko Ilija0https://orcid.org/0000-0003-3352-7637Nikolić Perica1https://orcid.org/0000-0001-7709-8139Matić Dragan2Bugarski Vladimir3https://orcid.org/0000-0001-6286-9287Faculty of technical science, Novi Sad, SerbiaFaculty of technical science, Novi Sad, SerbiaFaculty of technical science, Novi Sad, SerbiaFaculty of technical science, Novi Sad, SerbiaThis paper shows the optimization of the parameters of PI controllers in the application of vector control of a three-phase induction motor by genetic algorithm for the set optimality criterion. There is also the projecting procedure as well as the comparative analysis of the performances of speed estimator based on MRAS observer and speed estimator based on ANN. The basis of the research is a mathematical model of vector control of a three-phase induction motor, which was developed in MATLAB/Simulink. The experimental analysis of the results was carried on the laboratory model of electric motor drive based on the dSPACE card. The application of the encoder provides a smaller measurement error, whereas the application of estimators is possible in the cases for which pinpoint accuracy is not required and for which the price and/or reliability are of greater interest.https://scindeks-clanci.ceon.rs/data/pdf/1821-4487/2011/1821-44871104251K.pdfvector controlspeed estimationpi controllergenetic algorithmneural networkmrasdspace |
| spellingShingle | Kamenko Ilija Nikolić Perica Matić Dragan Bugarski Vladimir Induction motor control and speed estimation via adaptive and artificial intelligence method Journal on Processing and Energy in Agriculture vector control speed estimation pi controller genetic algorithm neural network mras dspace |
| title | Induction motor control and speed estimation via adaptive and artificial intelligence method |
| title_full | Induction motor control and speed estimation via adaptive and artificial intelligence method |
| title_fullStr | Induction motor control and speed estimation via adaptive and artificial intelligence method |
| title_full_unstemmed | Induction motor control and speed estimation via adaptive and artificial intelligence method |
| title_short | Induction motor control and speed estimation via adaptive and artificial intelligence method |
| title_sort | induction motor control and speed estimation via adaptive and artificial intelligence method |
| topic | vector control speed estimation pi controller genetic algorithm neural network mras dspace |
| url | https://scindeks-clanci.ceon.rs/data/pdf/1821-4487/2011/1821-44871104251K.pdf |
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