Yingbo Huang
Papers
6
Total Citations
315
H-Index
4
About
Yingbo Huang is a leading researcher in nonlinear robotic control, specializing in motion control, bilateral teleoperation, and adaptive systems. Their major contribution is the development of the Unknown System Dynamics Estimator (USDE), a simple yet efficient method for handling unknown dynamics and external disturbances in robotic systems, introduced in their highly cited 2019 paper (153 citations). This work has become a foundational tool for robust control. Huang further advanced the field with the Proportional-Integral Approximation-Free Control (PIAFC) approach (51 citations), which transforms motion tracking into system stabilization without requiring complex models. Their adaptive neural network control for robotic manipulators (92 citations) guarantees finite-time convergence, enhancing safety and precision. More recently, Huang has extended USDE to bilateral teleoperation systems with time-varying delays (13 citations), addressing critical challenges in remote robotics. Their work on prescribed-time tracking control (2 citations) pushes boundaries by achieving stability within user-defined timeframes. With over 300 total citations, Huang’s innovations in estimation and control continue to shape modern robotics, offering practical, high-performance solutions for uncertain environments.
Research Focus
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Top Papers
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