Automated Controller Design for the PMSM Using Dynamic Mode Decomposition

Abstract

This work presents a method to automatically generate a high performance controller for the permanent magnet synchronous motor (PMSM). The method consists of two components, a nominal system identification and a harmonic component identification. Both identification methods are based on dynamic mode decomposition (DMD). The nominal system identification is used to assign the feedback gaines by matching the desired closed-loop eigenvalues and eigenvectors. The harmonic system identification is used to generate vectors that are multiplied by a delay embedding of the current to predict harmonic components at the next time-step. The method is applied to two experimental test setups, one interior permanent magnet (IPM) and one surface mount permanent magnet (SPM) motor. It is shown that the automatically generated feedback controller is able to achieve a more precise transient response than the traditional rule-based PI controller. It is also shown the harmonic compensation method is able to reduce total demand distortion (TDD) on phase currents better than a traditional adaptive filter approach without the need for gain tuning. This work shows a novel approach to using DMD for the complete system identification of the PMSM, and lays the foundation for using DMD with delay embeddings to analyze and manipulate harmonic signals in a predictive way.