Computationally Efficient Finite-Set Model Predictive Current Control of Interior Permanent Magnet Synchronous Motors with Model-Based Online Inductance Estimation

In this paper, solutions to the main drawbacks of the traditional finite-set model predictive current control (FS-MPCC) of interior permanent magnet synchronous motors (IPMSM) are proposed. These drawbacks are: high computational load and high sensitivity to any model mismatch. The proposed computationally efficient FS-MPCC is based on finding the optimal voltage vector (VV) that would enhance the flow of the desired currents analytically. Based on its location in the stationary alpha-beta plane, only three iterations of a modified cost function will be needed. Furthermore, a novel model-based online inductance estimation technique is proposed to enhance the robustness of the controller against model mismatch.