Xuantao Gong
Papers
1
Total Citations
12
H-Index
1
About
Xuantao Gong is a leading researcher in nonlinear control systems and humanoid robotics, with a focus on robust adaptive strategies for complex, uncertain environments. His most cited work introduces a sliding mode nonlinear disturbance observer-based adaptive back-stepping control (ABSMC) algorithm, a pioneering contribution that enhances the stability and precision of humanoid robotic dual manipulators. By integrating a nonlinear disturbance observer, Gong’s approach effectively mitigates system uncertainties and external disturbances, enabling more reliable attitude control for robotic arms—a critical advancement for humanoid robots operating in dynamic, real-world settings. This work, published in 2018 and garnering 12 citations, underscores his impact in bridging theoretical control design with practical robotic applications. Gong’s research is instrumental for students and engineers developing resilient autonomous systems, offering a robust framework for addressing nonlinearities and uncertainties in mechatronic and robotic platforms. His contributions continue to influence adaptive control methodologies, particularly in humanoid robotics and nonlinear disturbance rejection.
Research Focus
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Top Papers
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