The research of loading model of eddy current dynamometer based on DRNN with double hidden layers

Since the loading model of eddy current dynamometer is difficult to establish as well as the experimental data may be insufficient in the process of modeling, this paper proposed a method, based on diagonal recurrent neural network (DRNN) with double hidden layers, to predict the data which can reflect system characteristics but can´t be measured by experiments, and then establish the loading model of eddy current dynamometer. Comparing the performance of DRNN with that of recursive least square (RLS) with forgetting factor method, this proposed model is much closer to the practical input and output characteristics of eddy current dynamometer. Appling it to control the loading system as a reference is conducive to the improvement of control precision and the enhancement of response characteristic.