Design and implementation of a novel model predictive control algorithm for Permanent Magnet Synchronous Machines

A novel Model Predictive Control (MPC) approach for Permanent Magnet Synchronous Machines (PMSMs) is proposed in this paper. It consists of choosing a number of MPC cost functions appropriately, in accordance with PMSM control strategy and torque requirements. These are then minimized following an appropriate order of priority, thus enabling enhanced MPC performances and flexibility compared to those achievable by employing weighting factors. Such a good result is achieved also by suitably managing PMSM operating constraints, over both dynamic and steady state operation. The effectiveness of the proposed MPC approach is validated through an experimental study, which refers to a Surface-Mounted Permanent Magnet Synchronous Machine (SPM) driven by means of a suitable control board. This consists mainly of Field Programmable Gate Arrays (FPGA), whose computational performances enable the real-time implementation of the proposed MPC algorithm.