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

Gai Liu and Huangqiu Zhu
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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

Energies, 2022, vol. 15, issue 5, 1-13

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.

Keywords: six-pole hybrid magnetic bearing; modified particle swarm optimization; least-squares support vector machine; displacement estimation method (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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