This article presents a neural network-based control method for maintaining the required output voltage of a synchronous buck converter. The goal was to replace a traditional PID controller with a neural network that calculates the duty cycle based on real-time data. Several versions of the neural network were tested. The final version, which included the input voltage, reference, and output current as inputs and compensated for dead time, was successfully validated on real hardware. It was able to respond to changes in load and input voltage within a limited operating range.