Modelling of induction motor using non-linear neural network system identification
F. Mohamed, Heikki N. Koivo · Society of Instrument and Control Engineers of Japan · 2004
This paper is concerned with the black box modelling of induction motor from test data. Data is obtained using a computer-based data acquisition card, the aim of the work described in this paper is to obtain model of the induction motor directly from test data. A pseudo random binary sequence (PRBS) was chosen as the test input signal. Data once collected was downloaded to the computer. The process of modelling and validation is then carried out using MATLAB nonlinear system identification toolbox. In this application, a model structure (NNARX) was assumed.