Unbalance Compensation and Automatic Balance of Active Magnetic Bearing Rotor System by Using Iterative Learning Control

Zheng, Yangbo; Mo, Ni; Zhou, Yan; Shi, Zhengang

doi:10.1109/access.2019.2938222

Cited by 29 publications

(17 citation statements)

References 26 publications

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“…Du et al [17] and Xu et al [18] investigated the electromagnetic aspects of the rotor AMBs systems. Zheng et al [19,20], Yao et al [21], and Gao et al [22] introduced different advanced control techniques to stabilize the lateral vibrations of the rotor AMBs system.…”

Section: Introductionmentioning

confidence: 99%

Radial Versus Cartesian Control Strategies to Stabilize the Nonlinear Whirling Motion of the Six-Pole Rotor-AMBs

et al. 2020

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Rotor active magnetic bearings system is the most efficient supporting technique of high-speed rotating machinery. This work aims to explore the dynamical behaviors of the 6-pole rotor active magnetic bearings system for the first time. Two different control strategies are introduced to mitigate the considered system lateral vibrations and the corresponding whirling motions. The first control technique (Radial control) is suggested such that the attractive magnetic force in each pole is proportional to both the radial displacement and radial velocity of the rotating disk toward that pole. The second control strategy (Cartesian control) is proposed such that the controlled magnetic force in each pole is designed to be proportional to both the cartesian displacement and cartesian velocity of the rotating disk in two perpendicular directions. Based on the proposed control strategies, two nonlinear dynamical models are derived and then analyzed by applying perturbation methods. Different response-curves and bifurcation diagrams are plotted utilizing the disk spinning-speed and the disk eccentricity as bifurcation control parameters. The main obtained analytical and numerical results illustrated that the considered system can perform a circular forward whirling motion only under the first control technique, while four whirling modes (that are forward whirling , backward whirling, both forward and backward whirling, and oscillation along a straight line) are noticed in the second control method depending on the disk spinning speed. Moreover, it is found that the radial control method is robust against the system instability than the cartesian control one, especially at large disk eccentricity. However, the cartesian control method could exhibit a vibration suppression efficiency higher than the radial control one at small disk eccentricity.

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Section: Introductionmentioning

confidence: 99%

Radial Versus Cartesian Control Strategies to Stabilize the Nonlinear Whirling Motion of the Six-Pole Rotor-AMBs

et al. 2020

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“…Then, three groups of simulation as shown in Table 2 are carried out for comparative analysis. The ILC parameters are set according to equations (31), (32), and (33), and k = 50 to distinctly observe the ILC process. The simulation results are shown in Figures 6 and 7.…”

Section: The Results Of Simulationmentioning

confidence: 99%

“…Certainly, there are other combinations. 31,32 From Figure 3, the iterative learning controller (ILC-2) described in equations (7), (31), (32), and (33) for AMB rotor unbalance control is applied in parallel with PID controller. There are many advantages using this parallel control mechanism, such as the existing CFCS can be used to stabilize the AMB system and suppress the non-periodic vibration disturbances, which can make up for the deficiency of ILC-2.…”

Section: Parallel Ilc Mechanism Based On Cfcsmentioning

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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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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“…When the coils are energized, electromagnetic forces in the corresponding direction will be generated to levitate the shaft to support it in the bearing cavity without contact. A synchronous radial force can be applied to the shaft to counterbalance the imbalance [134].…”

Section: Electromagnetic Actuatormentioning

confidence: 99%

A Review on Self-Recovery Regulation (SR) Technique for Unbalance Vibration of High-End Equipment

Pan

Huo

et al. 2020

Chin. J. Mech. Eng.

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The high-end equipment represented by high-end machine tools and aero-engines is the core component of the national intelligent manufacturing plan, and the mass unbalance is the main reason for its excessive vibration, that seriously impacts the operation efficiency and running life of the equipment. In order to change the traditional way that the fault of equipment can only be repaired by human, the self-recovery mechanism of human and animal are given to the equipment in this paper, which forms the self-recovery regulation (SR) system for unbalance vibration of high-end equipment. The system can online generate the self-recovery force to restrain the unbalance vibration of the equipment in operation, which is an important direction for the development of the equipment to the advanced intelligent stage. Based on the basic principles of SR technique, the typical engineering application cases of this technique in the field of aeroengine and high-end machine tools are introduced, and four related studies promoting the development of this technique are summarized and analyzed in turn. It includes feature extraction, imbalance location, regulation method and balancing actuator. Self-recovery Regulation (SR) Technique is an important way to realize intelligent manufacturing and intelligent maintenance. Relevant research can lay a technical foundation for the development of high-end equipment with self-health function.

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Unbalance Compensation and Automatic Balance of Active Magnetic Bearing Rotor System by Using Iterative Learning Control

Cited by 29 publications

References 26 publications

Radial Versus Cartesian Control Strategies to Stabilize the Nonlinear Whirling Motion of the Six-Pole Rotor-AMBs

Radial Versus Cartesian Control Strategies to Stabilize the Nonlinear Whirling Motion of the Six-Pole Rotor-AMBs

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 Review on Self-Recovery Regulation (SR) Technique for Unbalance Vibration of High-End Equipment

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