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This paper proposes an adaptive super-twisting algorithm based sliding-mode observer (STA-SMO) for surface-mounted permanent magnet synchronous machine (PMSM) sensorless control, in which voltage source inverter (VSI) nonlinearity is taken into consideration. An adaptive algorithm for online tuning the sliding-mode coefficients of STA-SMO is proposed based on the existing stable conditions. Thus, position estimation error can be reduced by the proposed adaptive algorithm in wide-speed range. Furthermore, voltage distortion due to VSI nonlinearity is online compensated to improve the accuracy of PMSM model. Because mismatch between reference and actual voltage due to VSI nonlinearity may bring large rotor position and speed estimation error, especially in low-speed range where distorted voltages may become dominant compared to actual voltages. Thus, a STA-SMO with adaptive sliding-mode coefficients and accurate voltage value could be obtained. Finally, the effectiveness of the proposed adaptive STA-SMO with online VSI nonlinearity compensation is verified on a surface-mounted PMSM by experiments.
Liang et al. (Fri,) studied this question.