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About

Jinglei Zhou is a control systems researcher whose work centers on intelligent control of robotic manipulators, with a particular focus on handling the real-world challenges of uncertainty, friction, and modeling errors that complicate precise robot motion. Spanning nearly two decades of scholarship, Zhou's research trajectory moves from foundational robust control methods to increasingly sophisticated adaptive and fuzzy logic-based frameworks. Early contributions, including work on friction compensation using linear state equations (2006–2007), established a rigorous mathematical basis for managing nonlinear robotic dynamics. Zhou's most impactful work emerged with the development of adaptive fuzzy controllers for uncertain robotic manipulators, with a 2018 study accumulating 18 citations and a 2022 paper on adaptive fuzzy backstepping control combined with dynamic surface control becoming the most widely cited work with 24 citations. This latter contribution is particularly notable for directly addressing the practical challenges of external disturbances and modeling inaccuracies encountered in operational environments. Collectively, Zhou's publications reflect a sustained commitment to bridging theoretical control design with applied robotics, offering solutions that improve trajectory tracking reliability in uncertain, real-world conditions.