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.
Highlights
T HIS work provides a generalizable methodology to automate the design of a current controller for the permanent magnet synchronous motor (PMSM)
[22] dynamic mode decomposition (DMD) was extended to handle nonlinear systems by allowing for augmented states. Both of these techniques are applied in this work to get a reliable model of the PMSM system including harmonic components
The PMSM system identification includes augmented states, actuation commands and measured speed, which do not transition from one time-step to the linearly
Summary
This work addresses some of the practical concerns that must be dealt with when applying DMD to motor controls This includes, removing the bias due to noisy measurements, handling the timevarying frequency of the system and actuation commands. It is shown that adding the proposed harmonic compensation method to a nominal feedback controller reduces the TDD at a given switching frequency. The DMD algorithm is constrained in that it only works on systems with constant frequencies This is fine for harmonic identification but the harmonic compensation must work at all operating speeds of the motor.
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