Induction motor drive with field-oriented control and speed estimation using feedforward neural network

The paper presents the results of our research on the use of artificial neural networks for sensorless control of induction motor drives. A feedforward artificial neural network with one hidden layer was designed and trained offline to act as a model of induction motor, which directly provides the actual speed of a drive. The model was subsequently incorporated in the field-oriented control scheme, where it fully replaces an incremental encoder. The presented solution was tested out using an experimental drive equipped with a 2.2 kW induction machine and controlled by a control system which is based on the TMS320F28335 digital signal controller. The obtained experimental results show a high level of accuracy in the low speed range.