Stabilizing model predictive control for torque control of permanent magnet synchronous motor

In this paper, we propose a simple model predictive controller (MPC) combined with a disturbance observer (DOB) for regulating the torque of a permanent magnet synchronous motor (PMSM) without steady state error. Specifically, a DOB is devised for estimating the unknown disturbance caused by a plant-model mismatch using a Luenberger observer. The proposed MPC minimizes a cost function at each time step in the receding horizon manner. It is possible to obtain the online optimal solutions without relying on a numeric algorithm using the specific property of the input matrix of PMSM. Thereafter, it is proven that the proposed MPC scheme ensures global asymptotic stability of the closed-loop system in the presence of input constraints and that the integrator in the DOB eliminates any offset error. Through the experiments, it is shown that the proposed MPC scheme provides satisfactory torque control performance.