Solar photovoltaic (PV) systems are becoming more and more popular since they immediately transform solar radiation into ecologically beneficial and sustainable electrical energy. It significantly lowers the system’s power output. To address this, continuous duty cycle variation methods that track a maximum power point under partial shading conditions have been proposed. In these schemes, proposed Luo converters are attached to the PV module to enable the highest output voltage under any given circumstance. A novel technique for Artificial Neural Network based Maximum Power Point Tracking (ANN-MPPT), which track Maximum Power Point (MPP) in the presence of further local maxima, has been integrated into the proposed system. The proposed technique tracks MPP by continuously varying a duty cycle of the converters without using expensive parts like signal converters and microprocessors, making the system more compact. Consequently, using the MATLAB 2021a/Simulink programme, we will do a number of numerical simulations to verify the proposed controls.