Bayarassou, HouriaMegri, Abderrahim FayçalBennour, Hachem2025-04-212025-04-212021http://dspace.univ-oeb.dz:4000/handle/123456789/21953Since the maximum power point (MPP) of a photovoltaic system changes with the changes in irradiation and temperature, an appropriate maximum power point tracking (MPPT) controller must be applied in the photovoltaic system. In this article, one of the powerful machine learning, support vector machine (SVM) is used as a predictive model, combining two traditional MPPT methods and the most commonly used: perturb and observation and incremental conductance to force photovoltaic systems to operate more efficiently In different weather conditions. The effectiveness of the proposed method is verified by Mathlab/Simulink simulation.enPV system ; MPPT: maximum power point tracking; SVM :support vector machine ; P&O: Perturb and Observe ; INC: Incremental ConductanceArticle