## 1 Introduction
These algorithms perform a comparative analysis under static and dynamic irradiation, considering the characteristics of the algorithm, such as MPP oscillations, tracking speed, and detection parameters. Significant research has been provided by [PERSON] and [PERSON] [9] concerning common maximum power point tracking (MPPT) algorithms. Their research seeks both approaches: perturbed and observed (P&O), and incremental conductance (InC). Therefore, they increase the inferior efficiency of the P&O and InC techniques by proposing new modified variants of these approaches. The output is notable by offering improvements related to tracking and the system's overall efficiency. Moreover, the time response is shorter than the time response of the original methods. [PERSON] and [PERSON] [10] proposed a modified incremental conductance (IC) algorithm for prompt and accurate MPP tracking. A comprehensive comparative study was conducted to test different features of their proposed technique against the classical approaches. The proposed model successfully addresses efficiency issues and significantly improves the output. In addition, [PERSON] and [PERSON] use a fully proportional deferential controller (PID) with a genetic algorithm (GA) to predict the variable step size of the IC-based MPPT technique. After the system was compared with the P&O MPPT, it proved to be more efficient in determining the global maximums (GM) for rapidly changing irradiance due to the parameters adopted on the GA basis of the regulator. [PERSON] and [PERSON] [11] work on an MPPT approach that combines fuzzy logic and neural networks with adaptive radial base function (RBF-NN). The proposed approach drives a DC-DC boost converter connected to a resistive load and PV module. The classical perturb and observe (P&O) algorithms are outperformed by the new approach, respectively, the incremental conductance (Inc) in energy conversion efficiency. [PERSON] and [PERSON] [12] modify a Perturb & Observe MPPT algorithm and use variable step size characteristics based on fuzzy logic to avoid the constraints associated with the traditional MPPT P&O tracking method. As a result, the attenuation of the transient regime improves the system's stability. For the testing part, the researchers use an indoor emulated photovoltaic source. The PV source contains a standard solar panel, a DC power supply, a DC-DC converter and an MPPT regulator provided by DSpace. Furthermore, the PV panel can be connected directly to the inverter to reduce costs and simplify the system, eliminating the DC-DC converter. [13]. The previous work also presents techniques illustrating the high-quality transit performance required in grid-connected scenarios with more than two PI controllers [13]. Thus, it is mandatory to fine-tune PI gains during the transient regime to achieve better efficiency. One of the most robust methods applied for PI gain setting is fuzzy logic control (FLC) [13]. Due to the simplicity and flexibility of FLC, it is used to control intelligent nonlinear systems and other complex applications. Considering the brief discussions above, the present research proposes developing a comparison between two different techniques to control a 150 W PV system under fluctuating irradiance circumstances and at a fixed temperature (25 \({}^{\circ}\)C) [14]. One of the approaches investigates incremental conductance MPPT, classic PI controllers with simple phase-locked loops (PLL). The second method stands for fuzzy MPPT with fuzzy PIs, and SOGI PLL. Both techniques use Clarke and Park Transformation in the control loop. The Clarke and Park Transformations adjust alternating physical quantities, being mandatory in the control of alternating current systems [14]. This paper is briefly structured as follows: Section 2 describes the PV Systems modeled in Matlab/Simulink and explains the designed PV array, inverter, MPPT algorithms, PI controllers, and grid synchronization PLL. Section 3 presents the results of the simulations and a comparison between the modeled systems.