Machine Learning-Based Secured Intelligent DMA Controller for Video Restoration

Abstract

Maximum power point tracking (MPPT) is an optimization algorithm for adjusting maximum power for DC/DC converters. SEPIC (single-ended primary-inductor converter) can allow the voltage to match the impedance between input and output. The perturbation and observation (P&O) method is a state-of-art tracking technique to maintain the voltage in photovoltaic (PV) systems. For this purpose, the adaptation of the P&O technique in economical digital devices can make sure of its efficiency and robustness. This paper was aimed at developing and designing an effective photovoltaic system based on the modified P&O algorithm with improved accuracy and power efficiency, thereby increasing the stability of a solar system. The performance of the proposed solar regulator system with two MPPT algorithms is verified using MATLAB simulator along with advanced modified P&O, and a hybrid excellence controller algorithm is also developed. The proposed system uses IoT-based sensors to transmit vital data to the cloud for remote monitoring and control purposes. The IoT platform helps the system to be viewed remotely.