Zhengjie Gao
Papers
10
Total Citations
171
H-Index
8
About
Zhengjie Gao is a robotics and control systems researcher whose work centers on hydraulic actuation and advanced control strategies for legged robots. His primary expertise lies in impedance control methodologies for hydraulic drive units (HDUs), the compact valve-controlled cylinder assemblies that power the joints of biologically inspired legged robots. Across a highly focused body of work, Gao has systematically developed and refined both position-based and force-based impedance control frameworks, contributing sensitivity analysis techniques—including first-order and second-order matrix methods—that help engineers understand and optimize control performance. His 2018 paper introducing an improved force-based impedance control method stands as his most influential contribution, accumulating 49 citations, while his broader portfolio has collectively shaped best practices in hydraulic legged robot control. Gao has also explored intelligent control strategies, including adaptive PID tuning via double-layer BP neural networks and fuzzy terminal sliding mode control with compound reaching laws, demonstrating a commitment to bridging classical hydraulic control theory with modern machine learning approaches. His dual-part dynamic compliance analysis series further illustrates his rigorous, systematic approach to understanding leg hydraulic drive system behavior. Gao's work offers an essential reference for researchers advancing the next generation of hydraulically actuated legged robotic platforms.
Research Focus
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Top Papers
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- 10Design and Application of MVIC for Hydraulic Drive Unit of Legged Robot3 citations · 2018