The flux-linkage characteristics of bearingless induction motors (BIMs) are nonlinear, and the models established by the general analytical method cannot accurately reflect the actual characteristics of BIMs. Thus, a novel method for nonlinear modeling of BIM flux linkage is proposed in this paper. The main objective of this method is to improve the accuracy of the flux linkage model based on the least square support vector machine (LSSVM) technique by applying the gray wolf optimization (GWO) algorithm to determine the optimal kernel parameter and regularization parameter of the LSSVM automatically. In this method, all BIMs flux linkage data are obtained from the finite-element method. In this paper, the relationship between input and output of the nonlinear flux linkage model is studied, and the precision model of GWO-LSSVM flux linkage is obtained. The simulation results demonstrate that the GWO-LSSVM model has high prediction accuracy and strong prediction ability. In addition, the GWO-LSSVM model is compared with other models. From this simulation comparison, it can be concluded that GWO-LSSVM modeling has the characteristics of higher accuracy. INDEX TERMS Bearingless induction motor, gray wolf optimization, least squares support vector machine, nonlinear model, finite element analysis.
The bearingless induction motor (BIM) system has the characteristics of non-linear, strongly coupled, and highly accurate. To achieve the stable and accurate control of BIM, the methods of direct torque control (DTC) and direct suspension force control (DSFC) based on space vector modulation (SVM) are introduced first. However, the dynamic performance and uncertain anti-jamming robustness of the system need to be further researched. Based on the BIM control system, the active disturbance rejection control (ADRC) technology is selected in this paper. The total disturbance of the system is estimated in real time by using the extended state observer (ESO). According to the estimated value of the ESO, the disturbance can be compensated by the ADRC in time to eliminate the steady-state tracking error to achieve good anti-interference performance. The ADRC-based direct torque and suspension force control system for the BIM is designed and simulated by the MATLAB software. The simulation and experiment results show that the ADRC technology can effectively suppress the impact of load disturbance, reduce the overshoot, and have strong robustness. INDEX TERMS Bearingless induction motor, active disturbance rejection control, space vector modulation, direct torque control, direct suspension force control.
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