## 2 Literature Review
### Solar Cells  
[PERSON] et al. [27] used an ANFIS controller and a super lift boost converter for MPPT in a PV system. [PERSON] and [PERSON] [28] used an ANFIS-PI controller for MPPT. In this study, the power generated by the PV cell was used to run a water pump and was not connected to the grid. [PERSON] et al. [29] used an ANFIS-based fractional order proportional-integral-derivative method to control a PV cell, which was connected to the grid through a DC-DC converter. [PERSON] et al. [30] used perturb-and-observe (P&O), fuzzy logic, and ANFIS methods for MPPT in a PV cell with a boost DC-DC converter. The output of the system was connected to the grid. [PERSON] et al. [31] used an ANFIS controller to control a PV cell and MPPT, where the particle swarm optimization (PSO) algorithm was used to design an ANFIS. The studied system included a brushless DC motor-based wire feeder unit. [PERSON] et al. [32] compared a fuzzy logic-based and an ANFIS approaches for MPPT and evaluated their stability and speed in reaching the MPP. The study showed that using an ANFIS with reduced rules can improve system efficiency. [PERSON] et al. [33] compared the performance of ANFIS-based MPPT methods with non-fuzzy methods, demonstrating the capabilities of ANFIS-based approaches. [PERSON] al. [34] proposed an ANFIS-based method for MPPT in a PV system. The method uses a DC-DC boost converter. The dynamic response of PV systems to grid fluctuations was compared to conventional PV systems, demonstrating its effectiveness. [PERSON] et al. [35] used an ANFIS and DC-DC boost converter combination to control a PV cell and battery system. The solution takes into account the effects of grid disturbances and the control system's ability to mitigate them. Additionally, MPPT was integrated into the control system. [PERSON] and [PERSON] [36] proposed an ANFIS-PID-Based MPPT controller system in a setup comprising a PV cell to charge an electric vehicle. [PERSON] et al. [37] used an ANFIS-assisted crowded plant height optimization for controlling a PV system under partial shading conditions. The control system employs a DC-DC boost converter. [PERSON] et al. [38] used two ANFIS controllers for fault detection and isolation and output control in a PV system. In a review article, [PERSON] et al. [39] examined various ANFIS methods employed to control PV systems. Among the discussed aspects were the types of converters used in controlling PV systems and the control objectives from the grid perspective. [PERSON] et al. [40] enhanced the performance of an MPPT system in a setup comprising a PV cell and a battery by combining an ANFIS and a hybrid crow-pattern search algorithm. The authors studied the environmental effects on the PV cell's output and their impact on the controller. [PERSON] et al. [41] used an ANFIS for MPPT. Additionally, the study included a DC-DC converter to connect the system to a DC grid. The capability of this solution under various weather and partial shading conditions was discussed. [PERSON] et al. [42] proposed a multi-input-output ANFIS-controlled solar-fuel-cell-based switched capacitor Z-source converter system for charging an electric vehicle. The system included a combination of a PV cell and a fuel cell to charge the vehicle's battery. [PERSON] et al. [43] built an organic solar supercapacitor structure for charging an electric vehicle. The control system was based on an ANFIS, and the employed converter was a pulse width modulation (PWM) DC-DC converter. [PERSON] et al. [44] studied the MPPT in a solar cell and battery system based on the sparrow search algorithm and an ANFIS. The suggested control system considers variations in solar irradiation, ambient temperature, and weather conditions. [PERSON] and [PERSON] [45] proposed an ANFIS controller for transient and voltage stability enhancement of an inverter in a PV system. This controller simultaneously performs MPPT.