## 3 Results
### Technical Analysis
#### 3.2.7 Assessing Efficiency and Improvements
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Reference** & **Description** & **Implementation** & **Efficiency** \\ \hline \multirow{3}{*}{[121]} & Voltage stability, active and reactive & _RT-LAB experiments_ & Efficiency testing considering diverse \\  & power control in island microgrid & _MATLAB/Simulink_ & operating states. \\  & Fuzzy adaptive impedance controller & _RT-LAB experiment (experimental platform hardware in loop)_ & Demonstrated by comparing the \\  & (virtual synchronous generator VSG strategy) for frequency and voltage & _MATLAB/Simulink_ & VSG control. \\  & stability & & \\ \hline \multirow{3}{*}{[123]} & Modified adaptive fuzzy control with & _Experimental setup_—APF _prototype_ & Simulation testing—Proposed method \\  & APF for power quality improvement & _with the proposed controller_ & versus two improved sliding-mode \\  & & _MATLAB/Simulink_ & control strategies. \\  & & _MATLAB/Simulink_ & Hardware testing—Efficiency testing \\  & & & considering various conditions. \\ \hline \multirow{3}{*}{[124]} & DPC is applied to parallel active & _Laboratory experimental setup_ & Simulation—Demonstrated by \\  & filtering using type-1 fuzzy & _MATLAB/Simulink_ & comparing the proposed method with \\  & to decrease THD & _MATLAB/Simulink_ & the conventional DPC strategy. \\  & & & Hardware—Before and after filtering. \\ \hline \multirow{3}{*}{[125]} & Harmonics mitigation using & _Laboratory implementation using_ & Software—Results obtained when \\  & three-level inverter-based APF & _digital signal processor and_ & considering APF + fuzzy control, APF \\  & controlled by fuzzy-based dwell-time & _experimental setup_ & without fuzzy, and without \\  & allocation algorithm (type-1 fuzzy) & _MATLAB/Simulink_ & APF:Hardware—Before and after \\ \hline \multirow{3}{*}{[126]} & Selective harmonic compensation & _Laboratory hardware testing_ & Proposed method vs. hysteresis, \\  & using microcontroller fuzzy-based control & _Laboratory hardware testing_ & “predictive 1” and “predictive 2” \\  & & control & control. \\ \hline \multirow{3}{*}{[127]} & Harmonics current compensation & _MATLAB/Simulink and_ & The proposed method’s results \\  & using APF controlled by three type-1 & _SimPowerSystems toolbox_ & compared the obtained results \\  & fuzzy controllers & _SimPowerSystems toolbox_ & simulating the system without the \\  & & & APF and fuzzy control. \\ \hline \multirow{3}{*}{[128]} & Fuzzy-PI current control of & _MATLAB/Simulink_ & Results obtained with the proposed \\  & DSTATCOM for power quality & _MATLAB/Simulink_ & method vs. results obtained using a \\  & improvement & & simple PI controller. \\ \hline \multirow{3}{*}{[129]} & Stability improvement in an island & \multirow{3}{*}{_DIgSILENT Power Factory software_} & \multirow{3}{*}{Proposed method vs. robust control.} \\  & microgrid using a battery storage & & \\  & system controlled by a fuzzy & & \\  & controller & & \\ \hline \multirow{3}{*}{[86]} & Harmonic current compensation & _MATLAB/Simulink_ & Results obtained with the proposed \\  & using hybrid power filter, P-Q theory, & _Hardware implementation using_ & method vs. results obtained using a \\  & and fuzzy control & FPGA & simple PI controller. \\ \hline \hline \end{tabular}
\end{table} 
Table 9: Relevant papers considering the implementation of fuzzy-based systems. Fuzzy logic's strength lies in its capability to work with the nonlinearities of complex systems and the fact that no mathematical description of the control process is necessary, so only the knowledge and experience of experts are needed to provide the data to build an operative FCS [131; 132]. However, a classic (type-1) FLC proved deficient when working in the presence of uncertainty factors [130].