Stator flux orientation inverse system decoupling control strategy of bearingless induction motor considering stator current dynamics

To handle the unbalanced vibration caused by uneven rotor mass distribution in a bearingless induction motor (BIM), a control strategy that integrates unbalanced feed-forward compensation and current compensation is presented. Firstly, based on the analysis of the BIM rotor vibration mechanism and the unbalanced vibration influence on the performance of the BIM, the dynamic model of the rotor is derived. Secondly, an unbalanced force feed-forward compensation controller is designed to extract the synchronous vibration signals through the synchronous signal detection unit, and then the compensation force components are generated by unbalanced feed-forward compensation controller. In addition, considering the influence of current in the rotor induced by suspension winding, a current compensation link is applied to the system to enhance the suspension performance. Finally, a rotor unbalanced vibration compensation control system of the BIM is established. The simulation and experimental results show that the proposed compensation control strategy not only can effectively reduce the rotor radial displacement and suppress the unbalanced vibration, but also can improve the suspension performance. INDEX TERMS Bearingless induction motor (BIM), current compensation, feed-forward compensation, radial displacement, rotor eccentricity.

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“…The radial suspension forces of the BIM in the x, y directions that are derived from Maxwell tensor method can be expressed as [42]- [44]:…”

Section: B Mathematical Model Of the Bimmentioning

confidence: 99%

Rotor Vibration Control of a Bearingless Induction Motor Based on Unbalanced Force Feed-Forward Compensation and Current Compensation

et al. 2020

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“…The controllable magnetic suspension force's generation principle is shown in Figure 1 [15,19], where the p 1 and p 2 equal to 2 and 1, respectively. Compared with a magnetic bearing motor, the BLM has unique advantages, such as a shorter shaft and a higher critical speed, etc., giving it bright application prospects in the high-speed-drive field [1,10,11,[21][22][23][24][25]. In all kinds of BLMs, because of the robust structure and larger stiffness coefficient of magnetic suspension force, the bearingless induction motor (BL-IM) has aroused wide attention [1,[6][7][8][9]12,13,[26][27][28].…”

Section: Introductionmentioning

confidence: 99%

Research on the Speed Sliding Mode Observation Method of a Bearingless Induction Motor

Chen

Qiao

2021

Energies

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In order to achieve the speed sensorless control of a bearingless induction motor (BL-IM), a novel sliding mode observation (SMO) method of motor speed is researched. First of all, according to the mathematical model of a BL-IM system, the observation model of stator current and that of rotor flux-linkage are derived. In order to overcome the chattering problem of a sliding mode observer, a continuous saturation function is adopted to replace the traditional sign function. Then, the SMO model of motor speed is derived, and the stability of the proposed motor speed SMO method is validated by the Lyapunov stability theory. At the end, the observed motor speed and rotor flux-linkage are applied to a BL-IM inverse “dynamic decoupling control” (DDC) system. Simulation results show that the real-time observation or dynamic tracking of motor speed and rotor flux-linkage are achieved in a more timely manner and more accurately, and higher steady-state observation accuracy is obtained; the proposed SMO method can be used in the BL-IM’s inverse DDC system to realize reliable magnetic suspension operation control without a speed sensor.

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“…The most common control methods for the BL-IM are vector control and direct torque control (Sun et al, 2019). In order to improve the dynamic response speed and suspension performance of the BL-IM, the stator current is decomposed into two components on the d -axis and q -axis to control the flux linkage and torque of the BL-IM respectively (Bu et al, 2019b). However, this method leads to the incomplete decoupling of the current components on the d - q axis and low anti-interference.…”

Section: Introductionmentioning

confidence: 99%

Predictive current control of a bearingless induction motor model based on fuzzy dynamic objective function

Yang

et al. 2020

Transactions of the Institute of Measurement and Control

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A control strategy for a bearingless induction motor (BL-IM) based on the fuzzy dynamic objective function is proposed in this paper. Firstly, based on the discrete mathematical model of the BL-IM, the stator current and flux linkage are predicted according to the given stator current and flux linkage, the objective function of model predictive current control (MPCC) is designed. Secondly, the fuzzy control algorithm is introduced in the objective function of the MPCC to dynamically assign the weighting factors before the current component on the d- q axis and the influence of the objective function on the performance of the BL-IM is analyzed under different weighting factors. By discretizing the rotational speed deviation Δ ω and rotational speed deviation rate, fuzzy reasoning is performed to obtain the optimal fuzzy dynamic function. Finally, the optimal fuzzy dynamic function is selected as the objective function of the MPCC to perform the simulations and experiments. The results show that the performance of the BL-IM under the MPCC strategy based on the fuzzy dynamic objective function is improved compared with the traditional MPCC and the vector control based on the fuzzy PID, due to its better dynamic and suspension performance. Meanwhile, the stability of rotor current component is enhanced.

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Stator flux orientation inverse system decoupling control strategy of bearingless induction motor considering stator current dynamics

Cited by 12 publications

References 25 publications

Rotor Vibration Control of a Bearingless Induction Motor Based on Unbalanced Force Feed-Forward Compensation and Current Compensation

Rotor Vibration Control of a Bearingless Induction Motor Based on Unbalanced Force Feed-Forward Compensation and Current Compensation

Research on the Speed Sliding Mode Observation Method of a Bearingless Induction Motor

Predictive current control of a bearingless induction motor model based on fuzzy dynamic objective function

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