Improved Self-Sensing Speed Control of IPMSM Drive Based on Cascaded Nonlinear Control

Abstract

This paper presents a nonlinear cascaded control design that has been developed to (1) improve the self-sensing speed control performance of an interior permanent magnet synchronous motor (IPMSM) drive by reducing its speed and torque ripples and its phase current harmonic distortion and (2) attain the maximum torque while utilizing the minimum drive current. The nonlinear cascaded control system consists of two nonlinear controls for the speed and current control loop. A fuzzy logic controller (FLC) is employed for the outer speed control loop to regulate the rotor shaft speed. Model predictive current control (MPCC) is utilized for the inner current control loop to regulate the drive phase currents. The nonlinear equation for the dq reference current is derived to implement the maximum torque per armature (MTPA) control to achieve the maximum torque while using the minimum current values. The model reference adaptive system (MRAS) was employed for the speed self-sensing mechanism. The self-sensing speed control performance of the IPMSM motor drive was compared with that of the traditional cascaded control schemes. The stability of the sensorless mechanism was studied using the pole placement method. The proposed nonlinear cascaded control was verified based on the simulation results. The robustness of the control design was ensured under various loads and in a wide speed range. The dynamic performance of the motor drive is improved while circumventing the need to tune the proportional-integral (PI) controller. The self-sensing speed control performance of the IPMSM drive was enhanced significantly by the designed cascaded control model.