Yongqing Fan

Papers

Total Citations

H-Index

About

Yongqing Fan is a researcher specializing in intelligent control systems, adaptive algorithms, and robotic manipulation, with a particular focus on addressing the challenges posed by uncertainty and nonlinear dynamics in complex mechanical systems. His most recognized work, "Fuzzy Adaptation Algorithms' Control for Robot Manipulators with Uncertainty Modelling Errors" (2018), demonstrates his innovative approach to bridging fuzzy logic theory with practical control engineering. In this contribution, Fan developed a novel fuzzy control scheme that introduces an adjustable parameter within the fuzzy logic system, enabling robot manipulators to function effectively as master devices within reference model dynamic frameworks — a significant step forward in handling uncertain nonlinear terms that traditionally hinder robotic precision and reliability. This work has accumulated 9 citations, reflecting growing recognition within the robotics and control systems community. Fan's research addresses a critical real-world challenge: making robotic systems more robust and adaptable in environments where modeling errors and unpredictable dynamics are unavoidable. His methodology offers meaningful implications for industrial automation, human-robot interaction, and intelligent systems design, positioning him as a contributing voice in the evolving field of adaptive fuzzy control for advanced robotics applications.