Simulation Based comparative study of AI (ANN) based voltage regulation of Buck - Boost converter with PI based Buck-Boost converter

This paper proposes a neural network control scheme of a DC-DC buck-boost converter using model reference control. In this technique, a dynamic back propagation algorithm is used. The controller is designed to stabilize the output voltage of the DC-DC converter and to improve performance of the Buck-Boost converter during transient operations. The general idea behind Model Reference Adaptive Control is to create a closed loop controller with parameters that can be updated to change the response of the system. The output of the system is compared to a desired response from a reference model. The numerical simulation results show that the proposed controller has a better performance compare to the conventional PI-Controller method.