A real-time neural network based controller for brushless DC motor drives

In this paper, a high performance controller with simultaneous real-time identification and control is developed for brushless de motors, The dynamics st the motor are modelled ''on-line'', and controlled using a three layer feed-forward artificial neural networks, as the system runs, Te control architecture adapts to the uncertainties of the motor dynamics and, in addition, learns their inherent nonlinearities. Extensive simulation studies were conducted and good performance of the brushless de motor as follow a number of reference tracks was observed, The simulations illustrated that a neuro-controller used in conjunction with adaptive control schemes can result in a flexible control device which may he utilized in a wide range of identification function is entirely separate from the control environments.