Particle Swarm Optimization Employed Machine Learning on MOSFET Based Ćuk Converter With Flying Squirrel Search Optimization (ML(PSO)-FSSO-Ćuk) Based MPPT

In this research work, particle swarm optimization (PSO) employed machine learning (ML) explore on MOSFET based Ćuk converter with Flying squirrel search optimization (FSSO) maximum power point tracking (MPPT) (ML(PSO)-FSSO-Ćuk) for higher photovoltaic (PV) power extraction. The ML(PSO)-FSSO- Ćuk based MPPT algorithm on Ćuk Converter delivers higher tracked efficacy with a minimized settling period. The PSO method provides training to ML for achieving optimal operation points which produces higher PV power from Ćuk converter. Also, the PSO method optimizes the weight of the artificial neural network (ANN) till the optimal operation point is achieved for the generation of Ćuk converter. Furthermore, the FSSO method achieves the best operation point for photovoltaic structures attached with Ćuk converter. The ML(PSO)-FSSOĆuk based MPPT approach and accomplished faster and more accurate PV power tracking on Ćuk converter with lesser computational load under changing environmental conditions.