Internal model control for reduction of bias and harmonic currents in hybrid magnetic bearing

Xu, Xiangbo; Liu, Jinhao; Shao, Chen

doi:10.1016/j.ymssp.2018.05.057

Cited by 13 publications

(6 citation statements)

References 27 publications

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“…The experimental results show that the method has a fast response speed and strong robustness. In order to overcome the bias and harmonic current interference caused by rotor gravity, mass unbalance, and sensor runout, Xu et al (Xu et al, 2019) proposed an internal model control method based on positive current feedback and gravity repeated control. The positive current feedback can adaptively adjust the rotor suspension position so that the force generated by the permanent magnet can accurately support the gravity of the rotor, and the repeated control can eliminate the harmonic current interference.…”

Section: Introductionmentioning

confidence: 99%

Influence of displacement sensor runout on active magnetic bearing-rotor system and control analysis

Jian

Cheng

2023

Journal of Vibration and Control

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In the active magnetic bearing (AMB)-rotor system, a displacement sensor is one of the indispensable components. It detects the displacement of the rotor in real time and feeds back to the control system to realize the stable suspension of the rotor. However, due to electromagnetic interference, unstable power supply, poor grounding, and uneven rotor surface, the signal runout of the displacement sensor can often occur, resulting in rotor vibration. Given the above problems, this paper establishes the control model of the AMB-rotor system, lists three typical sensor runout signals, then analyzes the influence of different types of sensor runout on the system, and discusses the control methods under different sensor runout conditions. The research results have a specific guiding significance for vibration control of the maglev rotor under sensor runout influence.

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Section: Introductionmentioning

confidence: 99%

Influence of displacement sensor runout on active magnetic bearing-rotor system and control analysis

Jian

Cheng

2023

Journal of Vibration and Control

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“…Virtual sensor fusion results in a higher order controller due to the inclusion of the virtual sensor dynamics. Virtual sensor fusion is fundamentally different from higher order control schemes like pole-placement [31], model-based control [32] and optimal control [33]. In virtual sensor fusion, the plant is made to resemble virtual sensor at higher frequencies where the dynamics of the plant are not well known.…”

Section: Introductionmentioning

confidence: 99%

Virtual sensor fusion for high precision control

Verma

Dehaeze

Zhao

et al. 2021

Mechanical Systems and Signal Processing

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High performance control requires high loop gain and large control bandwidth. However, the spurious resonances at the higher frequencies can limit the performance of such type of systems. This drawback can be overcome by using sensor fusion technique. In sensor fusion, two or more sensors are combined in synergy such that good performance is achieved at lower frequencies while ensuring robustness of the system at higher frequencies. This paper presents a new technique, termed as ''virtual sensor fusion", in which only one of the sensors is physically installed on the system while the other sensor is simulated virtually. The virtual sensor is selected based on desired high frequency response. The effectiveness of the proposed technique is demonstrated numerically for a case of active seismic isolation. A robustness analysis of virtual sensor fusion is also carried out in order to study its stability in the presence of spurious resonances. Finally, the technique is experimentally verified on active isolation of pendulum system from ground motion. The results obtained demonstrate good isolation performance at lower frequencies and robustness to plant uncertainties (spurious resonances) at higher frequencies. This technique can be effectively used for high precision control of sensitive instruments.

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“…Meanwhile, the unbalanced exciting force is at the same frequency as the rotational speed, and it causes unbalanced vibration of the rotor system. The unbalanced vibration force is proportional to the square of the rotational speed 11‐15 . When the motor runs at high speed, the rotor will not be able to suspend with stability and this case may even cause the friction between stator and rotor.…”

Section: Introductionmentioning

confidence: 99%

Rotor vibration unbalance compensation control of a bearingless induction motor

Yang

Jia

Sun

et al. 2021

Int Trans Electr Energ Syst

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Summary To handle the unbalanced vibration caused by the centroid deviation in a bearingless induction motor (BL‐IM), a dynamic unbalanced compensation strategy is proposed. Based on the traditional minimum force suppression, the best compensation value can be searched by combining with coordinate system algorithm. Firstly, the generating principle of radial suspension force and the mechanism of rotor vibration are analyzed. Then the mathematical model of dynamic imbalance compensation signal is established. Secondly, a preset compensation signal is applied to the suspension winding. The effective compensation signal that can reduce the rotor displacement is determined by measuring and calculating the corresponding variation in the rotor displacement. The effective compensation value is input into the adaptive iterative algorithm to keep approaching to the optimal compensation value. In addition, the coordinate search algorithm is used to ensure the speed and accuracy of the compensation signal calculation in the time‐varying system, which can realize the effective suppression of rotor vibration. Finally, the compensation control method is simulated in Matlab/Simulink toolbox and tested on a prototype designed by our research group. Both simulation and experimental results show that the time of motor reaching steady state is obviously shortened, and the radial deviation of the rotor is reduced during the operation of the motor. The unbalanced compensation method can effectively and quickly suppress rotor vibration.

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Internal model control for reduction of bias and harmonic currents in hybrid magnetic bearing

Cited by 13 publications

References 27 publications

Influence of displacement sensor runout on active magnetic bearing-rotor system and control analysis

Influence of displacement sensor runout on active magnetic bearing-rotor system and control analysis

Virtual sensor fusion for high precision control

Rotor vibration unbalance compensation control of a bearingless induction motor

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