For solar energy generated by High Concentration Photovoltaic and Concentrating Solar Power technologies, precise tracking systems are needed. Artificial Neural Network (ANN) and Maximum Power Point Tracking (MPPT) based Closed-loop systems utilise data supplied by a sun sensor, which takes up direct and diffuse sunlight. Increased measurement noise at the sensor's output due to diffuse sunlight reduces the maximum attainable gains in the closed-loop controller, resulting in decreased tracking performance. A four-quadrant photodiode solar sensor may be improved by using infrared and linear polarising optical filters. Regardless of the kind of controller used in the solar tracker, these filters limit the influence of diffuse radiation and increase the effectiveness of sun tracking systems. This paper presents tracking experiments including solar trackers under both indoor and outdoor situations, using various methods, such as Maximum Power Point Tracking (MPPT), as well as artificial neural networks (ANN).