Continuous Control Set Nonlinear Model Predictive Control of Reluctance Synchronous Machines

In this article, we describe the design and implementation of a current controller for a reluctance synchronous machine (RSM) based on continuous control set nonlinear model predictive control (NMPC). A computationally efficient gray box model of the flux linkage map, the Gaussian-linear-arctangent (GLA) model, is proposed and employed in a tracking formulation, which is implemented using the high-performance framework for NMPC
acados
. The resulting controller is validated in simulation and deployed on a
dSPACE real-time
system connected to a physical RSM. Experimental results are presented where the proposed implementation can reach sampling times in the range typical for electrical drives and can achieve large improvements in terms of control performance with respect to state-of-the-art classical control strategies.