Online Learning Artificial Neural Network Controller for a Buck Converter

This paper presents an Online Learning Artificial Neural Network Controller (OLANNC) for a DC-DC Buck converter. The proposed control scheme uses a Perceptron Online Learning algorithm to stabilize the output voltage. The OLANNC obtains the appropriate duty cycle of the PWM signal that determines the switching operation of the semiconductor device. To verify the effectiveness of the proposed method, a simulation results are presented with some operations such as reference voltage variations. Comparison with a typical controller is also presented to denote it advantages.