An Efficient Implementation of Online Model Predictive Control With Field Weakening Operation in Surface Mounted PMSM

Model-predictive-controller (MPC), one of the optimal control policies, has gained more attention in servo drive and other industrial applications in recent years due to evident control performance benefits compared to more classical control methods. However, an MPC algorithm solves a constrained optimization problem at each step that brings a substantial computational burden over classical control policies. This study focuses on improving the computational efficiency of an online MPC algorithm and then demonstrates its practical feasibility on the field weakening operation in high-speed PMSM control applications where the sampling frequency is in the order of <inline-formula> <tex-math notation="LaTeX">$\mu s$ </tex-math></inline-formula>. We implement the existing dual active set solver by replacing two standard methods in the matrix update step to reduce the overall computational cost of the algorithm. We also rearrange the linear approximation for the constraints on voltage and current by taking the tradeoff between accuracy and speed into account. We finally verify the efficiency and effectiveness of the proposed structure via processor-in-the-loop simulations and physical platform experiments.

Abstract licence: CC BY-NC-ND

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