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...

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Bibliographic Details
Published in:IEEE transactions on control systems technology 2022-01, Vol.30 (1), p.130-141
Main Authors: Zanelli, Andrea, Kullick, Julian, Eldeeb, Hisham M., Frison, Gianluca, Hackl, Christoph M., Diehl, Moritz
Format: Article
Language:English
Subjects:
Computational modeling
Controllers
Couplings
Electric motors
Mathematical model
Nonlinear control
nonlinear systems
Optimization
Predictive control
Reluctance
Stators
Switches
Synchronous machines
Torque
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Summary: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.
ISSN:1063-6536
1558-0865
DOI:10.1109/TCST.2020.3043956