Speed Sensorless Control for IPMSMs Using a Modified MRAS With Gray Wolf Optimization Algorithm

This article represents modified model reference adaptive system (MRAS) method for speed sensorless control of interior permanent magnet synchronous motor (IPMSM), which can estimate rotor speed and position information. To suppress the adverse effect of parameter variation on control performance, the stator resistance and the permanent magnet flux linkage are estimated and continuously updated in reference and adjustable model. Then, proportional-integral (PI) controller parameters of speed adaptive law obtained by MRAS are optimized by gray wolf optimization (GWO) algorithm. To get the smallest possible speed following error and reference current error, the objective function is designed with discretized rotor speed error and current error as variables. The simulation results show the better performance of rotor speed estimation is obtained with GWO algorithm.