Design and implementation of photovoltaic-assisted dynamic voltage restorer using fuzzy logic controller-based improved SOGI for power quality improvement

Fuzzy Control Systems for Power Quality Improvement—A Systematic Review Exploring Their Efficacy and Efficiency

“…When demonstrating the efficiency of the proposed methods described in their papers, researchers chose one or more of the following four strategies enumerated below to compare the results obtained using their control methods with the results obtained when (1) no control system was employed or no PQ improvement device was utilized [87], (2) a conventional PI, PID, or control method was used as the control system [111], (3) a simple (less efficient) version of the proposed method was employed [130], or (4) other methods proposed in similar studies from the literature were used [131].…”

“…The chart in Figure 9 illustrates the yearly distribution of the efficiency demonstrations of the four strategies enumerated above. As some papers contained more than one testing strategy [131], the number of methodologies is greater than the number of papers.…”

“…(less efficient) version of the proposed method was employed [130], or (4) other methods proposed in similar studies from the literature were used [131].…”

“…The chart in Figure 9 illustrates the yearly distribution of the efficiency demonstrations of the four strategies enumerated above. As some papers contained more than one testing strategy [131], the number of methodologies is greater than the number of papers. 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].…”

“…Figure 10 presents the results (number of papers per year) of the analysis of the final set in relation to the efficiency-improving methodologies used by the researchers in their studies. 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].…”