Sensorless technologies for the field-oriented control of the permanent magnet synchronous motors (PMSMs) are being actively developed today. Recently, a robust, nonlinear and globally convergent position observer for the surface-mount permanent magnet synchronous motor (SPMSM) has been proposed in [4]. The key feature of the robust observer is estimation of the rotor position requiring only the knowledge of the stator currents, voltages, resistance and inductance. However, the resistance and inductance of the stator may change during operation as a result of overheating, mechanical wear and environmental impacts. Thus, the aim of this study is to develop adaptive algorithms for the stator windings' parameters, which can be used for this position observer improvement. In this paper the authors propose four adaptive observers for estimation of the resistance and inductance at low motor speeds. It is assumed, that only currents and voltages of the stator windings are known. The other state variables and parameters of PMSM are unknown. The main idea of the synthesis of identification algorithms is linear filtering, which allows us to eliminate the unknown terms obtained by the mathematical transformations. Requirements to the external load, which ensure successful identification of the PMSM stator parameters, are given for each observer. The proposed adaptive observers for the stator resistance and inductance can be applied in case, when at low speeds, the field-oriented control of PMSM is carried out by means of Hall sensor, while at higher speeds, the sensorless control algorithms are used. A distinctive feature of the proposed estimation algorithms is that the resistance and inductance identification can be implemented during PMSM operation.