Papers
5
Total Citations
32
H-Index
3
About
Lu Wang is a robotics and control systems researcher whose work spans advanced motion control, space robotics, and human-robot interaction. With a career trajectory moving from mobile robotics to sophisticated space systems, Wang has made significant contributions to the development of robust, adaptive control frameworks for complex robotic platforms operating under challenging real-world constraints. Wang's most impactful contributions center on predefined-time and finite-time control strategies for flexible-joint space robots, addressing critical challenges such as actuator saturation, unknown dynamics, and external disturbances. A landmark 2024 study introducing nonsingular predefined-time dynamic surface control for flexible-joint space robots has already accumulated 10 citations, reflecting rapid community uptake. Complementing this, Wang's model-free adaptive robust control framework leveraging time delay estimation—garnering 9 citations since 2023—offers elegant solutions for robots with uncertain dynamics and input saturation without requiring precise system models. Beyond space robotics, Wang has explored human-robot interaction through sensorless variable impedance control and pioneered adaptive sliding mode approaches for mecanum-wheeled mobile robots. Collectively, Wang's portfolio demonstrates a consistent focus on bridging theoretical control innovation with practical robotic implementation, making their work particularly valuable for researchers tackling real-world autonomy and safety-critical robotic systems.
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