Synthesis of neuroregulator of power in system of sensorless traction electric drive
In this paper we solve the problem of synthesizing a power regulator in a traction electric drive system using artificial neural networks. To control the vehicle and obtain the desired quality of transients, neural network observers have been developed that allow the measurement of indirect par...
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| Format: | Article |
| Language: | English |
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Omsk State Technical University, Federal State Autonoumos Educational Institution of Higher Education
2021-04-01
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| Series: | Омский научный вестник |
| Subjects: | |
| Online Access: | https://www.omgtu.ru/general_information/media_omgtu/journal_of_omsk_research_journal/files/arhiv/2021/%E2%84%96%202%20(176)%20(%D0%9E%D0%9D%D0%92)/31-35%20%D0%90%D0%BD%D0%BE%D1%81%D0%BE%D0%B2%20%D0%92.%20%D0%9D.,%20%D0%9A%D0%B0%D0%B2%D0%B5%D1%88%D0%BD%D0%B8%D0%BA%D0%BE%D0%B2%20%D0%92.%20%D0%9C.,%20%D0%A1%D0%B0%D0%B8%D0%B4%D0%BE%D0%B2%20%D0%A1.%20%D0%90..pdf |
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| _version_ | 1832573977444220928 |
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| author | V. N. Anosov V. M. Kaveshnikov S. A. Saidov |
| author_facet | V. N. Anosov V. M. Kaveshnikov S. A. Saidov |
| author_sort | V. N. Anosov |
| collection | DOAJ |
| description | In this paper we solve the problem of synthesizing a power
regulator in a traction electric drive system using artificial
neural networks.
To control the vehicle and obtain the desired quality of
transients, neural network observers have been developed
that allow the measurement of indirect parameters to
determine the immutable coordinates of the system. For this
purpose, this paper uses dynamic neural networks. When
developing the neural network observer, experimental
data obtained by the authors on an operating vehicle in
real operating conditions are used.
To test the effectiveness of using the created artificial
neural network, an object is simulated with a random nature
of the supply voltage change. A comparative analysis of
transients in a system with a power neuroregulator and
classical regulators in a subordinate control system shows
a fairly high convergence of the results. |
| format | Article |
| id | doaj-art-795178ba9eb943d39323d86e5025ac84 |
| institution | Kabale University |
| issn | 1813-8225 2541-7541 |
| language | English |
| publishDate | 2021-04-01 |
| publisher | Omsk State Technical University, Federal State Autonoumos Educational Institution of Higher Education |
| record_format | Article |
| series | Омский научный вестник |
| spelling | doaj-art-795178ba9eb943d39323d86e5025ac842025-02-02T01:59:07ZengOmsk State Technical University, Federal State Autonoumos Educational Institution of Higher EducationОмский научный вестник1813-82252541-75412021-04-012 (176)313510.25206/1813-8225-2021-176-31-35Synthesis of neuroregulator of power in system of sensorless traction electric driveV. N. Anosov0V. M. Kaveshnikov1https://orcid.org/0000-0002-1427-0971S. A. Saidov2Novosibirsk State Technical UniversityNovosibirsk State Technical UniversityNovosibirsk State Technical UniversityIn this paper we solve the problem of synthesizing a power regulator in a traction electric drive system using artificial neural networks. To control the vehicle and obtain the desired quality of transients, neural network observers have been developed that allow the measurement of indirect parameters to determine the immutable coordinates of the system. For this purpose, this paper uses dynamic neural networks. When developing the neural network observer, experimental data obtained by the authors on an operating vehicle in real operating conditions are used. To test the effectiveness of using the created artificial neural network, an object is simulated with a random nature of the supply voltage change. A comparative analysis of transients in a system with a power neuroregulator and classical regulators in a subordinate control system shows a fairly high convergence of the results.https://www.omgtu.ru/general_information/media_omgtu/journal_of_omsk_research_journal/files/arhiv/2021/%E2%84%96%202%20(176)%20(%D0%9E%D0%9D%D0%92)/31-35%20%D0%90%D0%BD%D0%BE%D1%81%D0%BE%D0%B2%20%D0%92.%20%D0%9D.,%20%D0%9A%D0%B0%D0%B2%D0%B5%D1%88%D0%BD%D0%B8%D0%BA%D0%BE%D0%B2%20%D0%92.%20%D0%9C.,%20%D0%A1%D0%B0%D0%B8%D0%B4%D0%BE%D0%B2%20%D0%A1.%20%D0%90..pdftransport meanspower plantsartificial neural networksynthesis of regulatorsdc motorpower estimation |
| spellingShingle | V. N. Anosov V. M. Kaveshnikov S. A. Saidov Synthesis of neuroregulator of power in system of sensorless traction electric drive Омский научный вестник transport means power plants artificial neural network synthesis of regulators dc motor power estimation |
| title | Synthesis of neuroregulator of power in system of sensorless traction electric drive |
| title_full | Synthesis of neuroregulator of power in system of sensorless traction electric drive |
| title_fullStr | Synthesis of neuroregulator of power in system of sensorless traction electric drive |
| title_full_unstemmed | Synthesis of neuroregulator of power in system of sensorless traction electric drive |
| title_short | Synthesis of neuroregulator of power in system of sensorless traction electric drive |
| title_sort | synthesis of neuroregulator of power in system of sensorless traction electric drive |
| topic | transport means power plants artificial neural network synthesis of regulators dc motor power estimation |
| url | https://www.omgtu.ru/general_information/media_omgtu/journal_of_omsk_research_journal/files/arhiv/2021/%E2%84%96%202%20(176)%20(%D0%9E%D0%9D%D0%92)/31-35%20%D0%90%D0%BD%D0%BE%D1%81%D0%BE%D0%B2%20%D0%92.%20%D0%9D.,%20%D0%9A%D0%B0%D0%B2%D0%B5%D1%88%D0%BD%D0%B8%D0%BA%D0%BE%D0%B2%20%D0%92.%20%D0%9C.,%20%D0%A1%D0%B0%D0%B8%D0%B4%D0%BE%D0%B2%20%D0%A1.%20%D0%90..pdf |
| work_keys_str_mv | AT vnanosov synthesisofneuroregulatorofpowerinsystemofsensorlesstractionelectricdrive AT vmkaveshnikov synthesisofneuroregulatorofpowerinsystemofsensorlesstractionelectricdrive AT sasaidov synthesisofneuroregulatorofpowerinsystemofsensorlesstractionelectricdrive |