AUTHOR=Da-Wei Gong , Zhi-Qiang Qiu , Wei Zheng , Zhi-Wu Ke , Yang Liu 

TITLE=Intelligent Decoupling Control Study of PMSM Based on the Neural Network Inverse System

JOURNAL=Frontiers in Energy Research

VOLUME=10

YEAR=2022

URL=https://www.frontiersin.org/journals/energy-research/articles/10.3389/fenrg.2022.936776

DOI=10.3389/fenrg.2022.936776

ISSN=2296-598X

ABSTRACT=<p>This study obtains the analytical inverse system of a permanent magnet synchronous motor (PMSM) model based on the traditional magnetic field orientation decoupling control mode by analyzing the inverse quality of the PMSM. Using the neural network’s excellent approximation ability and well learning functions, a neural network inverse system (NNIS) of the decoupling control system was established by identifying and offline training the back propagation neural network (BPNN) and radial basis function neural network (RBFNN). The data collected from the analytical inverse system of the PMSM model are used to analyze and compare the prediction accuracy and running time of the neural network, so as to optimize the structure and parameters of the neural network. The simulation results of three PMSM decoupling control systems show that the PMSM decoupling control system based on RBF NNIS has good dynamic and static decoupling performance, and robustness.</p>