Voltage Tracking of a DC-DC Flyback Converter Using Neural Network Control

This paper proposes a neural network control scheme of a DC-DC Flyback converter that will step up a 12V DC and applied it on brushless DC motor with 12 and 24V dc. In this technique, a back propagation learning algorithm is derived. The controller is designed to track the output voltage of the DC-DC converter and to improve performance of the Flyback converter during transient operations. Furthermore, to investigate the effectiveness of the proposed controller, some operations such as starting-up and reference voltage variations are verified. The numerical simulation results show that the proposed controller has a better performance compare to the conventional PI-Controller method.