Sensorless Control of PMSM Based on an ANFIS Optimized Flux Sliding Mode Observer

doi:10.16182/j.issn1004731x.joss.21-0270

Abstract

Abstract:

Aiming at the low estimation accuracy of rotor speed and position and the system chattering in sensorless control of permanent magnet synchronous motor (PMSM), an adaptive neuro-fuzzy inference system (ANFIS) is proposed to optimize the flux sliding mode observer(FSMO). Compared with the traditional sliding mode observer, the FSMO improves the estimation accuracy of the rotor flux. The FSMO optimized by ANFIS realizes the on-line adjustment of the observer gain and reduces the system chattering. The improved PLL improves the estimation accuracy of the rotor speed and position. A simulation platform is established to verify the results which show that the ANFIS optimized FSMO can effectively improve the accuracy of the rotor speed and position estimation in PMSM sensorless control and reduce the system chattering.

Key words: flux sliding mode, adaptive neuro fuzzy inference system, phase locked loop, sensorless control, permanent magnet synchronous motor

CLC Number:

TP391.9

Huilin Zhang, Yujie Jin, Haima Yang. Sensorless Control of PMSM Based on an ANFIS Optimized Flux Sliding Mode Observer[J]. Journal of System Simulation, 2022, 34(8): 1682-1690.

Figures/Tables 11

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Table 1

Parameters of PMSM

参考变量	数值
阻尼系数B/(N·m·s)	0
极对数 $n p$	4
定子电感 $L s / m H$	8.5
定子电阻 $R s / Ω$	2.875
磁链 $λ f / W b$	0.175
转动惯量J/(kg·m²)	0.001

Table 1

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