2018
DOI: 10.1109/tpel.2017.2783920
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Adaptive Second-Order Sliding-Mode Observer for PMSM Sensorless Control Considering VSI Nonlinearity

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Cited by 319 publications
(117 citation statements)
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“…Unlike the decoupled-analyzing method in FOC, torque and flux linkage are controlled directly in DTC, therefore, the quickest dynamic response can be obtained in the PMSM driven by DTC [14][15][16]. However, as only six active vectors can be selected to compensate the errors of flux linkage and torque in conventional DTC, the PMSM suffers from some drawbacks, such as large torque and flux linkage ripples [17][18][19][20].…”
Section: Introductionmentioning
confidence: 99%
“…Unlike the decoupled-analyzing method in FOC, torque and flux linkage are controlled directly in DTC, therefore, the quickest dynamic response can be obtained in the PMSM driven by DTC [14][15][16]. However, as only six active vectors can be selected to compensate the errors of flux linkage and torque in conventional DTC, the PMSM suffers from some drawbacks, such as large torque and flux linkage ripples [17][18][19][20].…”
Section: Introductionmentioning
confidence: 99%
“…The study in [30] proposed sensorless control of PMSM with rotor position estimation based on tangent function-based phase-locked loop (PLL) structure and improved SMO with adaptive feedback gain related to the rotor speed. An SMO based on adaptive super-twisting algorithm was proposed in [31] for rotor position estimation of surface-mounted permanent magnet synchronous machine (SPMSM) and applied for sensorless control with compensation of voltage source inverter nonlinearity. The research conducted in [32] proposed sensorless control of IPMSM based on an SMO which utilized PLL technique and fuzzy control adjustment of sliding mode gain in order to reduce chattering and increase the observer robustness.…”
Section: Introductionmentioning
confidence: 99%
“…In [27,28], online parameters identifications were used to improve the estimate robustness. In [29][30][31], nonlinearity compensations were applied to reduce the estimated error. Adaptive filters were designed to filter out the undesired harmonic components in back EMF by analyzing the harmonic distribution of position estimated error, such as adaptive notch filter (ANF) [11], synchronous frequency extract filters (SFFs) [32], adaptive linear neural (ADALINE) filter [33], adaptive vector filter (AVF) [34], and so on.…”
mentioning
confidence: 99%