Model Reference Adaptive System of Permanent Magnet Synchronous Motor Based on Current Residual Compensation Without Position Measurement

Abstract

There exists an inaccurate measurement problem in permanent magnet synchronous motors (PMSMs) due to low motor speed operation, high temperatures and humid environments, which will degrade the motion performance and stability of PMSMs. In this study, a model reference adaptive system without position measurement is presented in a PMSM to improve the output performance with external disturbance suppression caused by an environmental change. Firstly, a PI adaptive estimation law is designed to identify the motor speed. Then, a optimization method based on the sliding mode variable structure technique is proposed to realize the stability augmentation of the speed loop by using the parametric fuzzy logic design. To reject the current loop noise, an extended Kalman filter (EKF) is adopted to compensate the input signal in the current loop. The effectiveness of this proposed method is verified via a numerical simulation in the case of different speeds and external loads.

Keywords

• permanent magnet synchronous motor (PMSM)
• model reference adaptive system (MRAS)
• sliding mode variable structure
• extended Kalman filter (EKF)
• fuzzy logic