Continuous Control Set Nonlinear Model Predictive Control of Reluctance Synchronous Machines

Abstract

In this paper we describe the design and implementation of a current controller for a reluctance synchronous machine based on continuous set nonlinear model predictive control. A simplified experimentally identified grey box model of the flux linkage map is employed in a tracking formulation which is implemented using the high-performance framework for nonlinear model predictive control acados. The resulting controller is validated in simulation and deployed on a dSPACE realtime system connected with a physical reluctance synchronous machine. Experimental results are presented where the proposed implementation can reach sampling times in the range typical for electrical drives and outperforms state-of-the-art classical control strategies.