Research on predictive control for PMSM based on online parameter identification

Abstract

Traditional PI controller has received a wide application for its simple structure and reliability. However, its proportion and integration parameter generally cannot be set too large to avoid overshoot. This restriction leads to degradation of dynamic performance, which is not expected in high-performance servo system. Therefore, searching for new control strategies is a trend to improve the dynamic performance at the same time to prevent appearance of overshoot. Predictive control strategy, which is based on the controlled object mathematical model, can achieve the theoretically fastest dynamic response. However, there is an inherent defect that it relies on the accurate mathematical model of the controlled object, which is usually difficult to obtain. Specific to high-performance servo system, real-time change of parameters of servo motor may occur, coupled with some non-ideal characteristics. All these factors restrict the predictive control strategy to play its best function. Aiming to improve the dynamic performance of permanent magnet synchronous motor servo system, this paper presents a predictive current control strategy based on on-line parameter identification of PMSM. Model reference adaptive system (MRAS) is employed to identify the parameters of PMSM. Based on the recognition results, predictive control strategy is adopted to control the dq axis current of the permanent magnet synchronous motor. In this way, the interference of parameter error is eliminated and perfect dynamic performance of the current loop is expected. Simulation and experimental results show that the predictive control method proposed here achieves very excellent dynamic response without overshoot. In addition, the automatic recognition of parameters leads to good robustness of the whole system.