An improved sliding mode model reference adaptive system observer for PMSM applications

Abstract

This paper introduces a sensorless control strategy of permanent magnet synchronous motors, termed the fast super twisting algorithm-based sliding mode improved model reference adaptive system observer (FSTA-SM-IMRASO). The proposed observer builds upon the conventional model reference adaptive system observer (MRASO) by incorporating a feedback correction term. Additionally, an adaptive feedback gain is devised to accommodate varying system operating conditions, thereby significantly enhancing the convergence speed of the error between the reference model and the adjustable model. Furthermore, a fast super twisting algorithm featuring an enhanced exponential term is devised and integrated with the model reference adaptive system theory, replacing the conventional PI controller used in MRASO. This integration leads to notable improvements in the system dynamic and static capabilities. Finally, the effectiveness of the proposed strategy is verified by simulation.