Current Sensorless Model Predictive Torque Control Based on Adaptive Backstepping Observer for PMSM Drives

摘要

A novel adaptive backstepping observer is proposed and model predictive torque control (MPTC) strategy is considered for three-phase permanent magnet synchronous motor (PMSM) drives without any current sensor. Generally, instantaneous stator currents are required for successful operation of MPTC. If the stator current sensors fail, the most common technique for reconstructing stator currents mainly focuses on using information from a single current sensor in the DC-link of an inverter. Nevertheless, the existence of immeasurable regions in the output voltage hexagon results in that the three-phase currents will not be reliably detected since one or more of the active state vectors are not applied long enough to insure accurate measurements. In addition, the technique may suffer from the very noisy of DC-link current feedback. To avoid these drawbacks, making use of the technique of adaptive backstepping, a novel observer is proposed. The designed observer can be capable of concurrent estimation of stator currents and resistance under the assumption that rotor speed and inverter output voltage as well as DC-link voltage are available for measurement. Stability and convergence of the observer are analytically verified based on Lyapunov stability theory. In order to reduce the torque & flux ripples and improve drives control performance, MPTC strategy is employed. The proposed algorithm is less complicated and its implement is relatively easy. It can ensure that the whole drives system achieves satisfactory torque & speed control and strong robustness. Extensive simulation validates the feasibility and effectiveness of the proposed scheme.