Design and Implementation of Neuro-Fuzzy Controller Using FPGA for Sun Tracking System

Abstract

Nowadays, renewable energy is being used increasingly because of the global warming and destruction of the environment. Therefore, the studies are concentrating on gain of maximum power from this energy such as the solar energy. A sun tracker is device which rotates a photovoltaic (PV) panel to the sun to get the maximum power. Disturbances which are originated by passing the clouds are one of great challenges in design of the controller in addition to the losses power due to energy consumption in the motors and lifetime limitation of the sun tracker. In this paper, the neuro-fuzzy controller has been designed and implemented using Field Programmable Gate Array (FPGA) board for dual axis sun tracker based on optical sensors to orient the PV panel by two linear actuators. The experimental results reveal that proposed controller is more robust than fuzzy logic controller and proportionalintegral (PI) controller since it has been trained offline using Matlab tool box to overcome those disturbances. The proposed controller can track the sun trajectory effectively, where the experimental results reveal that dual axis sun tracker power can collect 50.6% more daily power than fixed angle panel. Whilst one axis sun tracker power can collect 39.4 % more daily power than fixed angle panel. Hence, dual axis sun tracker can collect 8 % more daily power than one axis sun tracker.

A simple and low‐cost active dual‐axis solar tracker

“…If we compare our proposal with low‐cost microcontrollers implementation , the proposed DAST presents a high efficiency by using fewer components. Whereas, Ammar et al who have designed a DAST system based on NF Controller and obtained an efficiency of 50.6%, the implementation of such a system is not easy due to the use of complex algorithms that requiring an expensive controller (as FPGA), making the system more expensive. Moreover, we used servo motors for the motorization of the PV panel instead of stepper motors or DC motors as in that need an interface circuit to control the speed and the position, which increases the materials and the consumption of the energy.…”

“…Moreover, new methods for solar tracking have recently been introduced, using Artificial Intelligence (AI) such as fuzzy logic (FL), neural networks (NN), and neuro-fuzzy (NF). [47][48][49] For instance, Hamed in 50 designed and implemented a solar tracker system based on an FL controller. This system can collect about 24% more energy than a fixed panel.…”

A new Internet of Things based optimization scheme of residential demand side management system

“…However, the HEMS operation based on BPSO and BSA and augmented with ToU, CPP, RTP, simultaneous regulation are not investigated. In [31, 32] The authors introduced neuro‐fuzzy controller using FPGA for sun tracking system. However, in this reference, the researchers did not use a meta‐heuristic method to minimize the cost.…”