In this paper, a novel rotor speed estimation method using model reference adaptive system (MRAS) is proposed to improve the performance of a sensorless vector control in the very low and zero speed regions. In the classical MRAS method, the rotor flux of the adaptive model is compared with that of the reference model. The rotor speed is estimated from the fluxes difference of the two models using adequate adaptive mechanism. However, the performance of this technique at low speed remains uncertain and the MRAS loses its efficiency, but in the new MRAS method, two differences are used at the same time. The first is between rotor fluxes and the second between electromagnetic torques. The adaptive mechanism used in this new structure contains two parallel loops having Proportional-integral controller and low-pass filter. The first and the second loops are used to adjust the rotor flux and electromagnetic torque. To ensure good performance, a robust vector control using sliding mode control is proposed. The controllers are designed using the Lyapunov approach. Simulation and experimental results show the effectiveness of the proposed speed estimation method at low and zero speed regions, and good robustness with respect to parameter variations, measurement errors, and noise is obtained. terests include linear and nonlinear control theory, including sliding mode control, adaptive control, and robust control, with applications to electric drive and mechatronics systems.Mohammed Ouriagli received the Ph.D. degree in electrical engineering from the Institut National Polytechnique de Lorraine, Lorraine, France, in 1995.Since 2003, he has held a teaching position in automatic control in the Polydisciplinary Faculty of Taza, Université Sidi Mohamed Ben-Abdellah (USMBA), Taza, Morroco. His research interests mainly include linear and nonlinear control theory, including sliding mode control, adaptive control, robust control, electric drive applications, and mechatronics systems.
