Control and Parameter Estimation of PMSM by Runge-Kutta Model Based Predictive Control

Abstract

In this study, control and parameter estimation of a Permanent Magnet Synchronous Motor (PMSM) has been achieved by a relatively novel model predictive control method, which is referred to as the Runge-Kutta Model Based Predictive Control (RKMPC). Since PMSMs exhibit relatively nonlinear behavior and their parameter values are critical, they necessitate more robust control and parameter estimation than conventional control methods. Parameters of the PMSMs are subject to abrupt changes in load and temperature. These parameter fluctuations significantly affect the stability of the system. Therefore, in this study, beside the effective control of the system, an efficient parameter estimation has been established in the MATLAB/Simulink environment by RKMPC. The control and parameter estimation capability of RKMPC has been proven by simulation results.