<p>With the rapid development in the renewable energy sector, photovoltaic solar energy systems hold a prominent position among alternative energy sources, especially concerning their integration with electrical grids to achieve reliability and sustainability in energy supply. However, these systems still face complex technical challenges, the most prominent of which are the continuous fluctuations in environmental conditions, the non-linear response of the system, and the necessity to achieve optimal energy extraction while maintaining the quality and stability of the electrical grid. Recent literature indicates that traditional control strategies often lack the flexibility and ability to respond effectively to the dynamic changes that characterize photovoltaic systems. Therefore, recent scientific research has focused on developing advanced control schemes based on artificial intelligence techniques, primarily fuzzy logic, which has demonstrated high efficiency in dealing with uncertainty and the complexities of nonlinear modeling in solar energy systems. In this context, the importance of Maximum Power Point Tracking (MPPT) algorithms in grid-connected photovoltaic systems stands out, not only to maximize the benefit from solar energy but also to ensure compliance with grid standards in terms of voltage, frequency, and power quality. Studies have shown that integrating intelligent algorithms such as fuzzy logic with traditional MPPT techniques has led to significant improvements in system response and operational efficiency. Considering these changes and the increasing technical needs, recent research efforts have focused on innovating and developing advanced control techniques that address these challenges more effectively. Among the leading trends in this field are fuzzy logic-based sliding mode control (FLC-SMC) and fuzzy logic-based synergetic control (FLC-Synergetic). The results of the studies showed that FLC-SMC achieves a rapid dynamic response and high efficiency in tracking the maximum power point, despite its continued struggle with the oscillation problem that may affect the quality of the electrical current. In contrast, FLC-Synergetic demonstrated an advanced ability to reduce the phenomenon of oscillation and achieve greater system stability, especially under gradual changes in solar radiation, even if this sometimes came at the expense of response speed. The numerical results indicate that these advanced methods can achieve energy extraction efficiencies exceeding 98%, with a significant reduction in response time and distortion rates, making them ideal options for systems that require high-efficiency control and precise response to ensure network stability and the quality of the extracted energy. For example, fuzzy logic-based sliding control reduces dynamic errors and provides high system stability with an efficiency of up to 98% and a response time of 0.002&#xa0;s, with the total harmonic distortion (THD) of the current on the grid estimated at 4.79%. As for fuzzy-synergetic control, it is an advanced method that combines the flexibility of fuzzy control with speed and response accuracy, achieving an efficiency of up to 99.98% and a response time estimated at 0.0035&#xa0;s. The THD value of the current on the grid does not exceed 2.99%, reflecting a higher quality of energy achieved through this method. From here, the importance of comparative and analytical studies of these smart schemes emerges, with the aim of determining the optimal strategies for controlling grid-connected photovoltaic systems, especially in the face of changing and complex operating environments, thereby supporting the reliability and efficiency of solar energy as a sustainable power source in the future.</p>