Dynamic Performance Enhancement Method Based on Improved Model Reference Adaptive System for SPMSM Sensorless Drives

Abstract

Conventional sensorless drives usually suffer from an unsatisfactory dynamic response to the varying speed reference or load disturbance due to the design only for the speed estimator. In this paper, an improved adaptive law based model reference adaptive system (IAL-MRAS) algorithm is proposed to enhance the dynamic performance of a surface-mounted permanent magnet synchronous motor (SPMSM) sensorless drives, in which both a speed/position estimator and composite speed controller are designed by a systematic way. This improved adaptive law (IAL) incorporates both the mechanical and electromagnetic model to account for the mechanical factors on the speed variation, which can estimate the rotor position and load torque simultaneously. To further strengthen the disturbance rejection ability, a composite speed controller is designed based on the feedforward compensation scheme and IAL-MRAS. Meanwhile, a hybrid control strategy combining IAL-MRAS and $I$ - $f$ starting method is adopted to realize sensorless control in the full speed range. Comprehensive numerical simulation and experimental results have fully demonstrated that the proposed sensorless control strategy can achieve smaller settling time, stronger disturbance rejection ability, and less parameter tuning workload than those of the conventional methods.

Keywords

• Feedforward compensation
• improved adaptive law (IAL)
• model reference adaptive system (MRAS)
• sensorless control
• surface-mounted permanent magnet synchronous motor (SPMSM)