Model Predictive Speed Control of Permanent Magnet Synchronous Motor

Abstract

The PMSM system is a challenging, time-varying, nonlinear system. Various control methods have already been used to improve the PMSM's performance. The precise feedback linear control approach, which converts the novel nonlinear model into a linear model by suitable harmonize translation, is a logical choice given that the machine's dynamic model is nonlinear. This thesis presents new findings on the application of model predictive speed control of a permanent magnet synchronous motor, with the design based on a linearized state-space representation of the nonlinear model that describes the dynamics. The integral action used by the model predictive controller results in zero steady-state error and load torque disturbance rejection. The MPC is then compared to a standard approach, namely a Proportional Integral (PI) speed controller. The effectiveness of the approach is demonstrated by Simulink simulation results.