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Displacement Estimation of Six-Pole Hybrid Magnetic Bearing Using Modified Particle Swarm Optimization Support Vector Machine

Author

Listed:
  • Gai Liu

    (School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, China)

  • Huangqiu Zhu

    (School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, China)

Abstract

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.

Suggested Citation

  • Gai Liu & Huangqiu Zhu, 2022. "Displacement Estimation of Six-Pole Hybrid Magnetic Bearing Using Modified Particle Swarm Optimization Support Vector Machine," Energies, MDPI, vol. 15(5), pages 1-13, February.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:5:p:1610-:d:755375
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    Cited by:

    1. Mudassir Khan & A. Ilavendhan & C. Nelson Kennedy Babu & Vishal Jain & S. B. Goyal & Chaman Verma & Calin Ovidiu Safirescu & Traian Candin Mihaltan, 2022. "Clustering Based Optimal Cluster Head Selection Using Bio-Inspired Neural Network in Energy Optimization of 6LowPAN," Energies, MDPI, vol. 15(13), pages 1-14, June.

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