ANN Based Speed Control of a Solar Powered DC Motor

An Artificial Neural Network (ANN)-based method for accurate and effective speed control of a solar-powered DC motor is proposed in this research. The system uses a photovoltaic (PV) array to generate electricity, which is controlled by a DC-DC converter to guarantee maximum power point tracking (MPPT) in the presence of fluctuating solar radiation. Because of its capacity to adjust to changing environmental variables and nonlinear system dynamics, the ANN controller is intended to supplant conventional control techniques. In order to ensure optimal performance, the ANN is taught to manage the intricate interaction between input voltage, load variations, and motor speed. The suggested method is validated by simulation and experimental findings, which show better speed regulation, lower steady-state error, and quicker dynamic reaction than traditional PID controllers. The results demonstrate the resilience and effectiveness of the ANN-based controller, which makes it a promising solution for renewable energy-driven motor control applications.