Papers
3
Total Citations
46
H-Index
3
About
Jie Huang is a robotics and control systems researcher whose work centers on the precise modeling and control of electro-hydraulic actuators in legged robotic systems. His research tackles some of the most demanding challenges in dynamic robot locomotion, including time-varying parameters, high-frequency external disturbances, measurement noise, and unmeasurable system states — conditions that severely complicate real-world implementation of model-based controllers. Huang's most influential contribution, a 2020 paper on Model Predictive Trajectory Tracking Control (26 citations), introduced an adaptive robust optimal control scheme that integrates multi-scale online estimation to enable accurate, real-time trajectory tracking under complex operational constraints. Complementing this, his concurrent work on joint state and parameter estimation (14 citations) developed a data-driven multi-scale framework that satisfies the stringent real-time demands of advanced controllers — a critical step toward deploying intelligent legged robots in dynamic environments. His earlier work on feedback linearization sliding mode control (2018) laid important groundwork by addressing nonlinear force control challenges in single-joint hydraulic actuators. Collectively, Huang's contributions represent a coherent research program bridging advanced estimation theory, optimal control, and legged robotics, making him a notable emerging voice in high-performance hydraulic robot systems.
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