Papers
37
Total Citations
934
H-Index
16
About
Haoping Wang is a prominent researcher specializing in advanced control systems for robotic manipulators, rehabilitation exoskeletons, and mechatronic systems. His work centers on developing intelligent, model-free and model-independent control strategies that address real-world challenges such as parametric uncertainties, external disturbances, actuator faults, and nonlinear dynamics. Wang's most impactful contributions lie at the intersection of sliding mode control, time delay estimation, and adaptive neural network techniques. His 2019 paper on adaptive high-order terminal sliding mode control for robotic manipulators with backlash hysteresis has garnered 167 citations, establishing him as a leading voice in robust control design. Equally significant is his pioneering work on rehabilitation robotics, where he developed model-free fractional-order control frameworks for lower-limb exoskeletons and RBF neural network compensators for rehabilitation systems, collectively accumulating over 200 citations. More recently, Wang has advanced human-robot interaction control using series elastic actuators and enhanced extended state observers, reflecting his commitment to clinically relevant assistive technologies. His body of work, spanning fault-tolerant control, adaptive fuzzy systems, and compliant actuator design, demonstrates consistent innovation across nearly a decade of research, making him an essential reference for engineers and scientists working in intelligent robotics and rehabilitation engineering.
Research Focus
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Top Papers
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- 9Robust Adaptive Control of Robotic Manipulator with Input Time-varying Delay27 citations · 2019
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