Decoupling control of bearingless brushless DC motor using particle swarm optimized neural network inverse system
Neural network inverse system decoupling control can effectively solve the nonlinear strong coupling problem of bearingless brushless DC motor, but it has the problem of slow convergence and easy to fall into local extreme value. An Improved Particle Swarm Optimization (IPSO) algorithm has been empl...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Elsevier
2024-02-01
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| Series: | Measurement: Sensors |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S266591742300288X |
| _version_ | 1827373943744364544 |
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| author | Tao Tao Lianghao Hua |
| author_facet | Tao Tao Lianghao Hua |
| author_sort | Tao Tao |
| collection | DOAJ |
| description | Neural network inverse system decoupling control can effectively solve the nonlinear strong coupling problem of bearingless brushless DC motor, but it has the problem of slow convergence and easy to fall into local extreme value. An Improved Particle Swarm Optimization (IPSO) algorithm has been employed to optimize the initial weights of the BP neural network inverse system. Comparisons between traditional inverse system decoupling control and the proposed method through simulations were conducted to confirm the efficacy and superiority of the proposed decoupling strategy. Furthermore, experiment research indicates that effective decoupling control can be achieved for both speed and radial displacement, as well as between the x and y-axis radial displacements, showcasing the good dynamic decoupling performance and stability of the proposed decoupling control strategy. |
| first_indexed | 2024-03-08T11:25:09Z |
| format | Article |
| id | doaj.art-e3e83f1414ae4d92a21fbabc08aa3a4e |
| institution | Directory Open Access Journal |
| issn | 2665-9174 |
| language | English |
| last_indexed | 2024-03-08T11:25:09Z |
| publishDate | 2024-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Measurement: Sensors |
| spelling | doaj.art-e3e83f1414ae4d92a21fbabc08aa3a4e2024-01-26T05:34:45ZengElsevierMeasurement: Sensors2665-91742024-02-0131100952Decoupling control of bearingless brushless DC motor using particle swarm optimized neural network inverse systemTao Tao0Lianghao Hua1Corresponding author.; Yangzhou Polytechnic Institute, Yangzhou, 225127, ChinaYangzhou Polytechnic Institute, Yangzhou, 225127, ChinaNeural network inverse system decoupling control can effectively solve the nonlinear strong coupling problem of bearingless brushless DC motor, but it has the problem of slow convergence and easy to fall into local extreme value. An Improved Particle Swarm Optimization (IPSO) algorithm has been employed to optimize the initial weights of the BP neural network inverse system. Comparisons between traditional inverse system decoupling control and the proposed method through simulations were conducted to confirm the efficacy and superiority of the proposed decoupling strategy. Furthermore, experiment research indicates that effective decoupling control can be achieved for both speed and radial displacement, as well as between the x and y-axis radial displacements, showcasing the good dynamic decoupling performance and stability of the proposed decoupling control strategy.http://www.sciencedirect.com/science/article/pii/S266591742300288XBearingless brushless DC motorNeural network inverse systemDecoupling controlImproved particle swarm optimization algorithm |
| spellingShingle | Tao Tao Lianghao Hua Decoupling control of bearingless brushless DC motor using particle swarm optimized neural network inverse system Measurement: Sensors Bearingless brushless DC motor Neural network inverse system Decoupling control Improved particle swarm optimization algorithm |
| title | Decoupling control of bearingless brushless DC motor using particle swarm optimized neural network inverse system |
| title_full | Decoupling control of bearingless brushless DC motor using particle swarm optimized neural network inverse system |
| title_fullStr | Decoupling control of bearingless brushless DC motor using particle swarm optimized neural network inverse system |
| title_full_unstemmed | Decoupling control of bearingless brushless DC motor using particle swarm optimized neural network inverse system |
| title_short | Decoupling control of bearingless brushless DC motor using particle swarm optimized neural network inverse system |
| title_sort | decoupling control of bearingless brushless dc motor using particle swarm optimized neural network inverse system |
| topic | Bearingless brushless DC motor Neural network inverse system Decoupling control Improved particle swarm optimization algorithm |
| url | http://www.sciencedirect.com/science/article/pii/S266591742300288X |
| work_keys_str_mv | AT taotao decouplingcontrolofbearinglessbrushlessdcmotorusingparticleswarmoptimizedneuralnetworkinversesystem AT lianghaohua decouplingcontrolofbearinglessbrushlessdcmotorusingparticleswarmoptimizedneuralnetworkinversesystem |