Differential Evolution Based Nonlinear Model Predictive Speed Control of PMSM Implemented on GPU
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In this paper, the novel approach to the nonlinear model predictive speed control of a permanent magnet synchronous motor and its implementation is introduced. The implementation is performed using general-purpose computing on graphics processing unit. The introduced algorithm uses the optimization method based on the differential evolution to get the optimal increment of stator voltage. The proposed algorithm is tested in the processor in the loop simulation with the Simscape model for the simulation of PMSM and the Jetson Xavier embedded device for the algorithm execution. The results show the ability of the algorithm to ensure the reference tracking and to keep the requested variables within their limits.
Keywordsmodel predictive control, permanent magnet synchronous motor, differential evolution optimization, general-purpose computing, graphics processing unit, parallel computing
Document typePeer reviewed
SourceProceedings of 2021 IEEE 30th International Symposium on Industrial Electronics (ISIE) . 2021, p. 01-06.