## 10 Conclusions  
A new MPPT control algorithm was applied to get the MPP from a PV system. Under different operating conditions, the MPPT of the system was studied using different controllers. These controllers are the proposed MDOF-FLC, the SUI-PID controller, and the normal FLC to validate the proposed controller. The simulations in this study were conducted using MATLAB-implemented systems. The experimental work was performed to confirm the simulation results under the same conditions using the MicroLabBox dSPACE1202 platform, which performs the three controllers. Typhoon HIL-402 was used to emulate the hardware configuration. Simulation and experimental results show that the proposed MDOF-FLC controller has a 37.8% and 58.1% faster response with a better rise time compared to the SUIPID controller and the normal FLC, respectively. At the same time, the error, measured by the integral time absolute error (ITAE), was 29.4% and 62.5% lower, respectively. Also, the following conclusions can be extracted:1. The MPPT control algorithms increased the water supply flow rate at various irradiance levels. However, the MDOF-FLC has provided a slightly higher water flow rate than the SUI-PID and the FLC.
2. The MDOF-FLC provided a faster response and a better rise time. The MDOF-FLC reached a steady state at 2.3 milliseconds, the SUI-PID controller at 3.7 milliseconds, and the FLC at 5.5 milliseconds.
3. The MDOF-FLC, the SUI-PID controllers, and the normal FLC have a superior ability to track the PV panel MPP under sudden changes in irradiance levels and temperatures.
4. The MDOF-FLC is more suitable in the PV array or PV station system, which provides stable electricity for homes or other applications. It has more stability and a better rise time, resulting in a more efficient and accurate process.  
In future work, the study and analysis of the stability of the proposed MDOF-FLC will be considered, as it is one of the essential concepts in the analysis and design of control systems. The study of the stability of fuzzy control systems has been complex since fuzzy systems are nonlinear systems. Recently, stability analysis techniques based on nonlinear stability theory have been developed and need further study. In addition, study the effect of the partial shading conditions on the PV system to evaluate the proposed controller compared with other intelligent controllers. Also, it is possible to use another type of microcontroller, such as Arduino, instead of the MicroLabBox dSPACE1202 platform, as it is simpler to perform the three controllers.  
Conceptualization, M.F.E.-K. and M.-N.S.; methodology, M.F.E.-K.; software, M.F.E.-K.; validation, M.F.E.-K. and M.I.A.E.-S; formal analysis, M.F.E.-K.; investigation, M.F.E.-K.; resources, M.F.E.-K.; data curation, M.F.E.-K; writing--original draft preparation, M.F.E.-K.; writing--review and editing, M.F.E.-K., M.-N.S., M.I.A.E.-S. and S.A.M. visualization, M.F.E.-K.; supervision, M.-N.S., M.I.A.E.-S. and S.A.M.; project administration, M.F.E.-K.; funding acquisition, M.F.E.-K. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The authors declare no conflict of interest.