To address the problem of speed and flux observation in sensorless control of a bearingless induction motor under the influence of parameter changes and external disturbances, a speed sensorless control strategy combining radial basis function (radial basis function, RBF) neural network and fractional sliding mode is proposed. According to the current error, fractional sliding mode control rate is designed to reduce the speed-observed chatter of the bearingless induction motor and its adverse effect on the rotor suspension stability. Then, combined with the theory of RBF neural network, the new optimal control rate is obtained by using its approximation ability. At the same time, the stability of two control rate is proved. Thus, the flux linkage and speed under normal operation, parameter change and external disturbance are observed and the new speed sensorless control is realized. The simulation and experimental results show that the proposed joint RBF neural network approximation algorithm and fractional sliding mode speed sensorless control system of the bearingless induction motor can not only effectively identify the flux and speed under three conditions of no-load, load disturbance and speed change, but also ensure the good suspension of the motor rotor in the x-axis and y-axis directions.

Purpose The purpose of this paper is to address the large stator flux linkage ripple and electromagnetic torque ripple caused by the hysteresis comparator in traditional direct torque control for a bearingless induction motor (BIM). Design/methodology/approach Model predictive direct torque control (MPDTC) strategy is adopted. On the basis of the mathematical model of BIM, the stator current and stator flux observational values are obtained, and the electromagnetic torque and stator flux at the next moment are predicted. Then, based on the relationship between the stator flux and the electromagnetic torque, the predicted stator flux can be transformed into an equivalent flux linkage vector, which eliminates the weighting coefficients problem among multiple variables in traditional objective functions. The objective function and torque PI controller will output the optimal stator flux linkage and the increments of the torque phase angle. Through the phase angle increments, the space voltage vector can be obtained by the reference flux linkage controller instead of the stator flux linkage and the torque hysteresis controller. Findings The proposed MPDTC method can effectively improve the stator flux linkage and the torque ripple. It can implement the stable suspension of the rotor and improve the dynamic performance and steady-state accuracy of the BIM system. Originality/value A MPDTC strategy is proposed to reduce the ripple of stator flux and electromagnetic torque. The phase angle increment angle of stator flux linkage and electromagnetic torque is optimized by model prediction, and the optimal space voltage vector is obtained by designing the reference flux controller.

PurposeThe purpose of the control method proposed in this paper is to address the problem of the poor anti-interference of the suspension winding current in the traditional bearingless induction motor (BL-IM) direct suspension force control process.Design/methodology/approachA model predictive direct suspension force control of a BL-IM based on sliding mode observer is proposed in this paper. The model predictive control (MPC) is introduced to the traditional direct suspension force control to improve the anti-interference of the suspension current. A sliding mode flux linkage observer is designed and applied to the MPC system, which reduces the error of the parameter observation and improves the robustness of the system. The strategy is designed and implemented in the MATLAB/Simulink and the two-level AC speed regulation platform.FindingsThe simulation and experimental results show that the performance of the BL-IM under the control method proposed in this paper is better than that under the traditional direct suspension force control, and the suspension performance of the motor and the anti-interference of the control system are improved.Originality/valueThis study helps to improve the suspension performance of the motor and the anti-interference of the control system.

为了避免转速和电流传感器故障对无轴承异步电机(BAM)矢量控制系统中转速环、电流环以及悬浮控制的影响,提出了一种无轴承异步电机传感器故障容错控制策略.首先,设计扩张观测器实现对无轴承异步电机转速及误差的观测,利用数据融合策略来实现故障时转速的平滑切换,再根据转速观测误差设计合理阈值实现速度传感器的故障诊断及容错.其次,根据状态方程实现电流的观测,同时利用扩张观测器补偿状态方程的观察扰动,再根据电流观测误差设计合理阈值实现电流传感器的故障诊断及容错.最后的仿真和实验结果表明,所提出的无轴承异步电机传感器故障容错控制系统能在0.025 s内准确的实现转速和电流的故障诊断及容错控制,且其误差分别在±63 r/min和58 r/min以内,此外整个过程转子位移波动幅度在±38 μm以内,这表明转子能实现良好悬浮.

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.

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.

This paper deduces a unified mathematical model of open-circuit fault of six-phase induction machine, and purposes a fault-tolerence sensorless strategy based on the sliding mode observer(SMO) to estimate the rotor flux and rotor speed. In the proposed control scheme, the sliding mode observer is improved to achieve the rotor speed and rotor flux identification under healthy and arbitrary open circuit faults. The stability of the observer is proved by the Lyapunov function. The quasi proportional resonance (QPR) controller is introduced in the harmonic plane to suppress the harmonic current after the fault. The simulation and experiment results show that the proposed sensorless fault-tolerant control strategy based on sliding mode observer can accurately and effectively identify the rotor speed and rotor flux of the machine under normal and fault conditions.