ANN-Robust Backstepping MPPT Based on High Gain Observer for Photovoltaic System

Hind El Ouardi, Mohcine Mokhlis, Ayoub El Gadari, Youssef Ounejjar, Lahcen Bejjit

Abstract


A hybrid MPPT technique has been proposed in this paper for a standalone photovoltaic (PV) system. This technique is composed of two performant controllers, the first one, which is an intelligent method based on the Artificial Neural Network (ANN), is trained to rapidly estimate the optimum voltage under different changes of meteorological conditions, while the second one, that is the robust backstepping controller, is conceived to track the optimum voltage by offering high robustness against disturbances as well as the desired tracking criteria. To minimize the PV system cost, the required sensors’ number, their measurement error and the system complexity, a high gain observer (HGO) has been proposed and applied to estimate the state variables of the system by observing the boost inductor current, the PV voltage and the load voltage basing only on data provided by the control law and the PV current and voltage. The studied PV system was simulated in MATLAB/Simulink to verify its efficiency and robustness even under severe and different weather conditions.

Keywords


Standalone PV System;Boost Converter; Artificial Neural Network; Robust Backstepping; High Gain Observer.

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References


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DOI (PDF): https://doi.org/10.20508/ijrer.v13i3.14190.g8804

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