Fuzzy logic approach for controlling uncertain and nonlinear systems: a comprehensive review of applications and advances

This paper presents a comprehensive review of the latest developments in fuzzy logic (FL) applications across critical domains which include energy harvesting (EH), ambient conditioning systems (ACS), and robotics and autonomous systems (RAS), highlighting FL's capability to address nonlinearities and uncertainties in diverse technological environments. Through a detailed comparative analysis of research trends over the past decade, it underscores the increasing significance of FL in EH and RAS, contrasting with the sustained interest in ACS. Furthermore, the evaluation of different fuzzy inference systems across domains provides valuable insights into their specific strengths and limitations, aiding researchers and practitioners in making informed decisions aligned with their application needs. Additionally, the paper explores advanced modifications and hybridizations of FL, such as swarm intelligence and integrations with other control strategies, emphasizing the necessity for robust and adaptive FL systems. The review also identifies key open problems and potential research directions, such as the demand for adaptive FL systems in EH and advanced optimization techniques in ACS and RAS. Overall, this state-of-the-art review not only summarizes the current state of FL applications but also outlines a roadmap for future research, offering valuable insights for advancing FL's role in handling uncertainties and nonlinearities in complex systems.