Fast and Efficient Maximum Power Point Tracking Controller for Photovoltaic Modules
Volume 5, Issue 6, Page No 606-612, 2020
Author’s Name: Khalid Chennoufia), Mohammed Ferfra
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Department of Electrical Engineering, Mohammadia School of Engineers, Mohammed V University in Rabat, Rabat, PB765, Morocco
a)Author to whom correspondence should be addressed. E-mail: khalidchennoufi@research.emi.ac.ma
Adv. Sci. Technol. Eng. Syst. J. 5(6), 606-612 (2020); 
DOI: 10.25046/aj050674
Keywords: Artificial Neural Network, Backstepping, MPPT, Double diode model, SEPIC
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This paper presents an efficient Maximum Power Point Tracking (MPPT) controller for photovoltaic modules. The MPPT technique consists of a combination between backstepping controller and artificial neural network (ANN).The (ANN) has been employed to generate the optimum voltage, which corresponds to the maximum power voltage delivered by photovoltaic modules, while the backstepping controller is developed to track the generated voltage, by computing the duty cycle of the Single Ended Primary Inductor Converter (SEPIC). The control of the boost converter is based on Lyapunov stability analysis, and an integral action is added to increase system robustness. In order to prove the accuracy of the developed control a comparison between the proposed method and sliding mode was carried out. In addition the stability was evaluated under sudden variation of environmental conditions. The simulation was carried out in MATLAB software, the results shows that the proposed controller tracks the reference voltage within 25 ms, in addition the systems reacts to sudden environments change with no oscillations, which demonstrate the robustness of the proposed method.
Received: 31 July 2020, Accepted: 06 November 2020, Published Online: 24 November 2020
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