An Improved Sensorless Control of Permanent Magnet Synchronous Motorized Spindle Based on ADALINE Dead-Time Compensation Algorithm

In order to address issues such as stator current distortion and increased harmonics caused by the dead-time effect in power devices of permanent magnet synchronous motorized spindle (PMSMS), a sensorless control strategy with dead-time compensation based on an adaptive linear neuron (ADALINE) neural network bandpass filter (NNBPF) is proposed. First, this paper introduces a neural network extended state observer phase-locked loop (NNESO-PLL) based on NNBPF, in conjunction with a stator flux observer to realize a position sensorless control strategy capable of suppressing high-order harmonics. Second, NNBPF is utilized to extract 5th and 7th harmonic components of α-β axis currents, and the least mean square (LMS) algorithm is employed to adaptively adjust the weights. The modulated linear neuron output vector serves as feedforward compensation voltage, aiming to suppress current harmonics and mitigate the impact of the dead-time effect. Finally, the proposed sensorless and dead-time compensation sensorless control strategy is compared with traditional sensorless control methods under the influence of dead-time effects. Experimental results verify that the proposed strategy effectively suppresses current harmonics, reduces current distortion, and achieves stable rotor speed tracking.