Automatic learning control for unbalance compensation in active magnetic bearings

Bi, Chen; Wu, Dezheng; Jiang, Quan; Liu, Zhejie

doi:10.1109/tmag.2005.851866

Cited by 76 publications

(13 citation statements)

References 11 publications

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“…Most research results on the AMB rotor unbalance control need to extract the periodic components of the signal, but unfortunately most of them only described the algorithm theory and did not analyze the existing problems from the perspective of digital control system. [11][12][13][14][15][16][17][18][19][20][21] However, we found PCEA based on Fourier transform theory would occupy numerous computing resources, which ultimately cannot meet the real-time requirement of the control system.…”

Section: Problem Formulationmentioning

confidence: 99%

“…Therefore, most of unbalance control methods need to extract periodic components from the rotor displacement signal directly or indirectly. As mentioned in previous studies, [11][12][13][14][15] the process of the periodic component extraction algorithm (PCEA) is basically divided into two steps: the first step is to calculate the coefficients of the frequencies to be extracted using the Fourier transform theory and the second step is to synthesize the periodic signals with respect to the frequencies using the inverse Fourier transform theory. This seems to be a very simple process but it takes numerous digital signal processing (DSP) computing resources in the AMB digital control system due to calling of the sine and cosine functions repeatedly.…”

Section: Introductionmentioning

confidence: 99%

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A novel iterative learning control method and control system design for active magnetic bearing rotor imbalance of primary helium circulator in high-temperature gas-cooled reactor

Zheng

Liu

Zhao

et al. 2020

Measurement and Control

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As one of the key technologies of high-temperature gas-cooled reactor, primary helium circulator–equipped active magnetic bearing provides driving force for primary helium cooling system. However, repetitive periodic vibration produced by rotor imbalance may introduce risks to primary helium circulator (even for high-temperature gas-cooled reactors). First, this article analyzes a periodic component extraction algorithm which is widely used in active magnetic bearing rotor unbalance control methods and points out the problem that the periodic component extraction algorithm occupies numerous computing resources which cannot satisfy the real-time request of active magnetic bearing control system. Then, a novel iterative learning control algorithm based on the iteration before last iteration of system information (iterative learning control-2) and a plug-in parallel control mechanism based on the existing control system are put forward, meanwhile, an integrated independent distributed active magnetic bearing control system is designed to solve the problem. Finally, both the simulation and experiment are carried out, respectively. The corresponding results show that the control method and control system proposed in this article have significant suppression effect on the repetitive periodic vibration of the active magnetic bearing system without degrading the real-time requirement and can provide important technical support for the safe and stable operation of the primary helium circulator in high-temperature gas-cooled reactor.

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Section: Problem Formulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A novel iterative learning control method and control system design for active magnetic bearing rotor imbalance of primary helium circulator in high-temperature gas-cooled reactor

Zheng

Liu

Zhao

et al. 2020

Measurement and Control

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show abstract

“…Active magnetic bearings are usually built in five degrees of freedom (DOFs), with two radial translational DOFs, two radial torsional DOFs, and an axial translational DOF. The unbalanced factors, including vibration, external noises, and non-alignment between the mass center and the geometric center, could lead to runout of the rotor (Bi et al, 2005). Each of the translational DOFs can be an explicit single-degree-of-freedom (SDOF) model controlled by active electromagnets, while the control current operating the exogenous force is applied on the bearings.…”

Section: Problem Formulationmentioning

confidence: 99%

“…Therefore, control schemes need to be applied for adjustment of the electromagnet voltages, because it can easily be seen that the system is an unstable open loop. However, for most traditional control schemes like the proportional-integral-derivative (PID) controller, system runout would occur in certain initial conditions in a real system, caused by the non-alignment of the geometric center and mass center (Bi et al, 2005). Iterative learning schemes, referred to as ILC, can actively stabilize the system by refining the control input from the error information obtained by the previous cycle.…”

Section: Problem Formulationmentioning

confidence: 99%

Disturbance rejection via iterative learning control with a disturbance observer for active magnetic bearing systems

Tang

et al. 2019

Frontiers Inf Technol Electronic Eng

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Although standard iterative learning control (ILC) approaches can achieve perfect tracking for active magnetic bearing (AMB) systems under external disturbances, the disturbances are required to be iteration-invariant. In contrast to existing approaches, we address the tracking control problem of AMB systems under iteration-variant disturbances that are in different channels from the control inputs. A disturbance observer based ILC scheme is proposed that consists of a universal extended state observer (ESO) and a classical ILC law. Using only output feedback, the proposed control approach estimates and attenuates the disturbances in every iteration. The convergence of the closed-loop system is guaranteed by analyzing the contraction behavior of the tracking error. Simulation and comparison studies demonstrate the superior tracking performance of the proposed control approach.

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“…A LQR scheme for vibration control in AMB system to reduce the unbalance vibrations is proposed by Arias, et al [5]. Moreover, iterative learning control is applied in the unbalance compensation for AMB system [6][7][8][9][10]. However, most of the existing methods to reduce the rotor unbalance vibrations in AMB system are based on the control system, which may to some extent influence the AMB system stability In this paper, a series of assault blocks are added to the rotor system.…”

Section: Introductionmentioning

confidence: 99%

Influences of Assault Blocks on Rotor Vibrations in AMB System

Zhu¹,

Zhang²

2015

TOEEJ

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In an active magnetic bearing (AMB) system, the rotor always rotates at extremely high speed which always accompany with huge vibrations and noises. Most of the former researches associated with reducing the rotor vibrations are mainly focused on the control methods of AMB. A new method of installing series of assault blocks in the rotor is proposed to reduce the rotor vibrations. Firstly, the dynamic models of rotor supported by AMB considering the influences of assault blocks are established. Then, both dynamic simulations with and without assault blocks are carried out separately using the real-time AMB support dynamic stiffness. The rotor vibration displacements are mainly analyzed. Finally, relevant experiments are made to verify the theoretical results. Both theoretical and experimental results validated the advantages of using assault blocks.

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Automatic learning control for unbalance compensation in active magnetic bearings

Cited by 76 publications

References 11 publications

A novel iterative learning control method and control system design for active magnetic bearing rotor imbalance of primary helium circulator in high-temperature gas-cooled reactor

A novel iterative learning control method and control system design for active magnetic bearing rotor imbalance of primary helium circulator in high-temperature gas-cooled reactor

Disturbance rejection via iterative learning control with a disturbance observer for active magnetic bearing systems

Influences of Assault Blocks on Rotor Vibrations in AMB System

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