Employment of a progressive learning neural network for identification and control: theory and numerical tests

This paper describes an innovative control technique for a DC electric drive when adaptation is to be taken into account. After a short overview of nonlinearities typical of electric machines, a neural-adaptive method based on the identification of the inverse model, is proposed for the control of such drives. The neural network adopted is a kind of clustering network, called the progressive learning network. Finally, simulations results are shown.