Displacement Estimation of Six-Pole Hybrid Magnetic Bearing Using Modified Particle Swarm Optimization Support Vector Machine
In order to solve the problems of the large volume and high cost of a six-pole hybrid magnetic bearing (SHMB) with displacement sensors, a displacement estimation method using a modified particle swarm optimization (MPSO) least-squares support vector machine (LS-SVM) is proposed. Firstly, the inerti...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-02-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/15/5/1610 |
| _version_ | 1797475285031976960 |
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| author | Gai Liu Huangqiu Zhu |
| author_facet | Gai Liu Huangqiu Zhu |
| author_sort | Gai Liu |
| collection | DOAJ |
| description | In order to solve the problems of the large volume and high cost of a six-pole hybrid magnetic bearing (SHMB) with displacement sensors, a displacement estimation method using a modified particle swarm optimization (MPSO) least-squares support vector machine (LS-SVM) is proposed. Firstly, the inertial weight of the MPSO is changed to achieve faster iterations, and the prediction model of an LS-SVM-based MPSO is built. Secondly, the prediction model is simulated and verified according to the parameters optimized by the MPSO, and the predicted values of MPSO and PSO are compared. Finally, static and dynamic suspension experiments and a disturbance experiment are carried out, which verify the robustness and stability of the displacement estimation method. |
| first_indexed | 2024-03-09T20:42:55Z |
| format | Article |
| id | doaj.art-92349b44353749b585e254a386aacb38 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-09T20:42:55Z |
| publishDate | 2022-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-92349b44353749b585e254a386aacb382023-11-23T22:54:49ZengMDPI AGEnergies1996-10732022-02-01155161010.3390/en15051610Displacement Estimation of Six-Pole Hybrid Magnetic Bearing Using Modified Particle Swarm Optimization Support Vector MachineGai Liu0Huangqiu Zhu1School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, ChinaSchool of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, ChinaIn order to solve the problems of the large volume and high cost of a six-pole hybrid magnetic bearing (SHMB) with displacement sensors, a displacement estimation method using a modified particle swarm optimization (MPSO) least-squares support vector machine (LS-SVM) is proposed. Firstly, the inertial weight of the MPSO is changed to achieve faster iterations, and the prediction model of an LS-SVM-based MPSO is built. Secondly, the prediction model is simulated and verified according to the parameters optimized by the MPSO, and the predicted values of MPSO and PSO are compared. Finally, static and dynamic suspension experiments and a disturbance experiment are carried out, which verify the robustness and stability of the displacement estimation method.https://www.mdpi.com/1996-1073/15/5/1610six-pole hybrid magnetic bearingmodified particle swarm optimizationleast-squares support vector machinedisplacement estimation method |
| spellingShingle | Gai Liu Huangqiu Zhu Displacement Estimation of Six-Pole Hybrid Magnetic Bearing Using Modified Particle Swarm Optimization Support Vector Machine Energies six-pole hybrid magnetic bearing modified particle swarm optimization least-squares support vector machine displacement estimation method |
| title | Displacement Estimation of Six-Pole Hybrid Magnetic Bearing Using Modified Particle Swarm Optimization Support Vector Machine |
| title_full | Displacement Estimation of Six-Pole Hybrid Magnetic Bearing Using Modified Particle Swarm Optimization Support Vector Machine |
| title_fullStr | Displacement Estimation of Six-Pole Hybrid Magnetic Bearing Using Modified Particle Swarm Optimization Support Vector Machine |
| title_full_unstemmed | Displacement Estimation of Six-Pole Hybrid Magnetic Bearing Using Modified Particle Swarm Optimization Support Vector Machine |
| title_short | Displacement Estimation of Six-Pole Hybrid Magnetic Bearing Using Modified Particle Swarm Optimization Support Vector Machine |
| title_sort | displacement estimation of six pole hybrid magnetic bearing using modified particle swarm optimization support vector machine |
| topic | six-pole hybrid magnetic bearing modified particle swarm optimization least-squares support vector machine displacement estimation method |
| url | https://www.mdpi.com/1996-1073/15/5/1610 |
| work_keys_str_mv | AT gailiu displacementestimationofsixpolehybridmagneticbearingusingmodifiedparticleswarmoptimizationsupportvectormachine AT huangqiuzhu displacementestimationofsixpolehybridmagneticbearingusingmodifiedparticleswarmoptimizationsupportvectormachine |