Active Disturbance Rejection Decoupling Control for Three-Degree-of- Freedom Six-Pole Active Magnetic Bearing Based on BP Neural Network

Wang, Shaoshuai; Zhu, Huangqiu; Wu, Mengyao; Zhang, Weiyu

doi:10.1109/tasc.2020.2990794

Cited by 44 publications

(22 citation statements)

References 5 publications

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“…Zhong, et al [23] also used NSGA-II to optimize a HOMB actuator and its controller, with a two-stage control approach utilized, which used different PD controllers for the rotor levitation/startup, and at a steady state operating speed with unbalance. Modern controls like active disturbance rejection control [32,33], robust control [34][35][36], sliding mode control [37][38][39], repetitive control [40,41], neural network control [42] have been applied into magnetic bearing supported systems. However, when it comes to optimization design of the magnetic system, most researchers still use conventional PID controller.…”

Section: Discussionmentioning

confidence: 99%

A Review of Active Magnetic Bearings Supported Systems Optimization Design

Wan¹

2020

Int J Magnetics Electromagnetism

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Section: Discussionmentioning

confidence: 99%

A Review of Active Magnetic Bearings Supported Systems Optimization Design

Wan¹

2020

Int J Magnetics Electromagnetism

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“…4. 126 sequence values corresponding to node vector U, such as 10,11,12,13,14,15,17,18,19,20,21,23,24,25,26,27,29,30,31,32,33,35, were selected as training samples. The corresponding node vector U of sequences 16,22,28,34,40,46,52,58,64,70,76,82,88,94,100,106,112,118,124,130,136,142 were selected as the test sample.…”

Section: A Simulation Study Of Aeroengine Buffer Surfacementioning

confidence: 99%

“…Although the BP neural network can deal with nonlinear parameters, it has some shortcomings and limitations [20], [21]. For example, in the selection of node vector samples, it is required that node vectors must be representative.…”

mentioning

confidence: 99%

An Improved Method for NURBS Surface Based on Particle Swarm Optimization BP Neural Network

Tian

Kong

et al. 2020

IEEE Access

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In order to further improve the accuracy and speed of the present commonly used NURBS surface method, an improved method for NURBS surface based on particle swarm optimization BP neural network is proposed. Firstly, node vectors of the data points are calculated by using the parametrization method of accumulating chord length. Then, prediction model of node vectors is constructed by using the particle swarm optimization BP neural network, and the experiment is presented to justify the feasibility and veracity of constructed prediction model. Finally, using the predicted node vectors, a fast and highprecision NURBS surface is realized. The results showed that the root mean squared error of fitting result of surface was deduced 84.05% and the run time was deduced 92.42% compared with the traditional NURBS method. Therefore, the proposed method is a fast and high-precise NURBS surface fitting method.

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“…To increase the stability of magnetic bearings, an accurate mathematical model is established in [9]. Although the three-pole magnetic bearing has many advantages, it also increases the overall design and cost of the system in [10]. A six-pole magnetic bearing is proposed, and the nonlinear and coupling problems of three-pole magnetic bearings are solved [11].…”

Section: Introductionmentioning

confidence: 99%

Analysis for Six-Pole Outer Rotor Hybrid Magnetic Bearing

Liu¹,

Zhu²

2022

PIER Letters

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In order to solve the nonlinear and coupling problems of three-pole hybrid magnetic bearing, a six-pole outer rotor hybrid magnetic bearing (HMB) is proposed. Firstly, the structure and working principle of the six-pole outer rotor HMB are introduced. Secondly, the linearity and coupling characteristics curves between radial suspension force and control current are analyzed and verified by the finite element method. In comparison with the analysis results of the three-pole HMB, there is no electromagnetic coupling between radial two degrees of freedom of the six-pole outer rotor HMB, and the nonlinear problem of force-current characteristic is solved. Finally, an experimental platform is built. The research results show that the maximum bearing capacity of the six-pole outer rotor HMB is 32.3% higher than that of the three-pole HMB. The suspension force-current characteristic experiment shows that the suspension force-current properties of the six pole outer rotor hybrid magnetic bearing can be considered linear near the equilibrium position, and there is no magnetic coupling between two radial degrees of freedom of the six pole outer rotor HMB near the equilibrium position. Nomenclature HMB Hybrid magnetic bearing OSHMB Outer-rotor six-pole hybrid magnetic bearing THMB Three-pole hybrid magnetic bearing PM Permanent magnet DSP Digital signal processing A11, A12, A21, A22 Magnetic poles of A phase B11, B12, B21, B22 Magnetic poles of B phase C11, C12, C21, C22 Magnetic poles of C phase F xThe suspension force in the x direction F yThe suspension force in the y direction i xThe control current in the x direction i yThe control current in the y direction

show abstract

Active Disturbance Rejection Decoupling Control for Three-Degree-of- Freedom Six-Pole Active Magnetic Bearing Based on BP Neural Network

Cited by 44 publications

References 5 publications

A Review of Active Magnetic Bearings Supported Systems Optimization Design

A Review of Active Magnetic Bearings Supported Systems Optimization Design

An Improved Method for NURBS Surface Based on Particle Swarm Optimization BP Neural Network

Analysis for Six-Pole Outer Rotor Hybrid Magnetic Bearing

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