Radial Displacement Sensorless Control of Permanent Magnet Assisted Bearingless Synchronous Reluctance Motor in Full Speed Range

The displacement sensors utilized in the control system of the permanent magnet assisted bearingless synchronous reluctance motor (PMa-BSynRM) are associated with high cost and low reliability. To address this, this paper proposes a radial displacement sensorless control method in the full speed range. Firstly, the rotor suspension principle is expounded, and the voltage and current equations of the system are derived. Secondly, in the low speed range, the rotor displacement is estimated using high frequency square wave injection (HFSWI) combined with a phase-locked loop (PLL) for accurate signal demodulation. Thirdly, a left inverse observer is constructed using an improved radial basis function (RBF) neural network, and the initial parameters of the neural network are optimized by the weighted mean of vectors algorithm (INFO), ultimately achieving accurate displacement estimation. Furthermore, the transition boundaries between operational modes are determined through deceleration simulation, incorporating a weighted fusion algorithm to guarantee seamless switching across speed regions. Finally, the proposed approach is verified through simulation and comparative experiments. Experimental results demonstrate a maximum steady-state estimation error of 7 μm, while the settling time extends by only 11 ms under external disturbances. Overall, the proposed method exhibits superior estimation precision and robust disturbance rejection capability.