Modeling and Implementation of a Proximal Policy Optimization Algorithm for Non-Inverting Buck-Boost Converter Control

This paper presents a novel approach to controlling non-inverting buck-boost converters using Proximal Policy Optimization (PPO) algorithm for renewable energy applications, particularly photovoltaic systems. Traditional PID controllers face significant limitations when dealing with the complex nonlinear dynamics, external disturbances, and varying operating conditions inherent in renewable energy systems. The proposed PPO-based control strategy addresses these challenges by providing adaptive and intelligent control capabilities. Through comprehensive simulation and experimental validation, we demonstrate that the PPO algorithm successfully learned optimal control policies within 10,000 episodes, maintain excellent voltage regulation under various operating conditions. The results confirm the effectiveness of the proposed approach in maintaining stable output voltage regulation under varying load conditions, input voltage fluctuations, and temperature variations.