Papers
11
Total Citations
555
H-Index
9
About
Donghui Cao is a prominent researcher specializing in electro-hydraulic servo systems, robotic excavators, and intelligent motion control. His work sits at the intersection of control theory, robotics, and construction automation, with a particular focus on solving the complex nonlinear challenges inherent in hydraulic machinery. Cao's most influential contribution — an adaptive sliding mode controller integrating RBF neural networks for electro-hydraulic servo systems — has garnered over 212 citations, establishing him as a leading voice in intelligent hydraulic control. A recurring theme throughout his research is the characterization and compensation of nonlinear friction, a critical obstacle in achieving precise trajectory tracking in robotic excavators. His development of advanced friction models that account for both velocity and pressure dependencies, moving beyond traditional LuGre limitations, reflects his commitment to real-world engineering accuracy. Beyond friction compensation, Cao has made meaningful strides in system identification, adaptive impedance control for dynamic contact force tracking, and multi-objective trajectory optimization balancing time, energy, and impact. His work on human-excavator cooperative systems and flexible virtual fixtures further highlights his interest in bridging human operators with intelligent autonomous machinery. With over 550 total citations and a publication record spanning foundational modeling to applied robotics, Cao's research is shaping the future of intelligent construction automation.
Research Focus
Key Achievements
Top Papers
- 1
- 2Parameters identification and trajectory control for a hydraulic system88 citations · 2019
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- 6Flexible virtual fixtures for human-excavator cooperative system28 citations · 2019
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