학술논문

Continuous Control Set Nonlinear Model Predictive Control of Reluctance Synchronous Machines
Document Type
Periodical
Source
IEEE Transactions on Control Systems Technology IEEE Trans. Contr. Syst. Technol. Control Systems Technology, IEEE Transactions on. 30(1):130-141 Jan, 2022
Subject
Signal Processing and Analysis
Communication, Networking and Broadcast Technologies
Computing and Processing
Robotics and Control Systems
Computational modeling
Switches
Stators
Torque
Optimization
Couplings
Mathematical model
Electric motors
nonlinear systems
predictive control
Language
ISSN
1063-6536
1558-0865
2374-0159
Abstract
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.