## 5 Conclusions  
This paper presents a comprehensive review of fuzzy-based control system applications for PQ improvement, highlighting the importance of efficacy demonstration, efficiency assessment, and improvement for FCSs. A proposed literature classification outlines seven criteria for evaluating papers that examine the characteristics of FCSs and PQ issues. The classification also presents statistics and tendencies in this area. Additionally, the most pertinent papers are selected and described in detail to provide a comprehensive overview of the subject matter.  
Control systems that use hybrid fuzzy control and employ adaptive functions, optimization algorithms, and self-tuning techniques have been found to provide the best results for addressing specific issues. Such approaches have been proven to be superior to conventional and simpler fuzzy-based control methods.  
To ensure the effectiveness of FCSs, it is crucial to conduct efficacy testing using a combined approach of simulations and experimental tests. This approach provides a more comprehensive understanding of the system's performance, which is essential for ensuring the safety and reliability of FCSs. To enhance the efficiency of FLCs, it is important to explore all features and inference strategies and make sure they are the right choice for the application. To demonstrate the efficiency of the proposed methodologies, it is imperative to explore the various simulation methods mentioned in the literature and conduct experimental tests that cover a range of scenarios. By doing so, we can gain valuable insights that can help us optimize our processes and achieve better results.  
This study has relevant implications not only for researchers, but also for participants. From an academic point of view, the main contributions of this paper are linked to the characteristics of fuzzy-based control systems, in particular, aspects regarding the structure, features, and inference strategies of FLCs, as well as combinations of fuzzy logic and other techniques that increase the performance of control systems. Additionally, the paper presents an analysis of the literature regarding efficiency testing, thus helping researchers in understanding new directions and tendencies. From a practitioner's viewpoint, this work presents studies from a more practical point of view, focusing on PQ issues and control devices, and including studies that describe experimental implementations and prototypes.  
In conclusion, maintaining PQ within standard limits is crucial for power systems. However, due to the unpredictable and nonlinear nature of power systems, it is challenging to achieve this. Fuzzy logic, along with optimization techniques and adaptive strategies, is an appropriate approach for improving PQ. This work aims to simplify the understanding and use of fuzzy logic control in power quality issues and power quality control devices.  
Regarding future directions for research, we consider further assessing published research that focused on power quality control using ANFIS and similar methodologies (data-driven fuzzy-based control) that were omitted in this research.  
Conceptualization, A.M. and A.C.C.; methodology, A.M.; validation, A.M., A.C.C. and H.G.B.; formal analysis, A.M. and H.G.B.; investigation, A.C.C.; resources, A.M.; data curation, H.G.B.; writing--original draft preparation, A.M. and H.G.B.; writing--review and editing, A.C.C.; visualization, H.G.B.; supervision, A.C.C.; project administration, A.M. All authors have read and agreed to the published version of the manuscript. This research received no external funding. This work was supported by a grant from the Ministry of Research, Innovation and Digitalization, CCCDI--UEFISCDI, project number PN-III-P2-2.1-PED-2021-4309, within PNCDI III. The authors declare no conflicts of interest. The authors declare no conflicts of interest.