Modeling and identification of Wiener nonlinear system based on fractional order filter and BiGRU neural network
LI Feng
YANG Yue-song
LI Sheng-quan
Abstract：In this paper,modeling and identification method of Wiener nonlinear system based on fractional order filter and bi-directional gated recurrent unit(BiGRU)neural network is proposed,and applied to current and voltage prediction of permanent magnet synchronous motors.Firstly,the unknown coefficient of the fractional order filter is computed by the Grünwald-Letnikov method,and then the filter is utilized to filter the input data to remove the high frequency noise and enhance the robustness of the data.Secondly,in order to improve the ability to capture the deeper features of the sequences,the BiGRU neural network is used to simultaneously acquire the past and future information of the sequence data,and the parameters of the BiGRU network are updated by an adaptive momentum estimation technique.Simulation results show that the proposed Wiener system could effectively model the permanent magnet synchronous motor system and achieve better prediction results.Compared with the integer order filter BiGRU neural network,the mean square error of the voltage prediction value is reduced by 30.87％and the mean absolute error is reduced by 26.97％,the mean square error of the current prediction value is reduced by 34.42％and the mean absolute error is reduced by 14.88％.
Keywords：nonlinear Wiener systemfractional order filtersbidirectional GRU neural networksparameter identifica-tionpermanent magnet synchronous motor
Publication Date：2025-06-30
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：10( 1181-1190 )