Chenbo Yin
Papers
14
Total Citations
719
H-Index
9
About
Chenbo Yin is a prominent researcher specializing in electro-hydraulic servo systems, robotic excavator control, and intelligent control algorithms, with a career spanning from humanoid robotics to advanced construction automation. His work has made substantial contributions to the fields of nonlinear control, friction modeling, and trajectory planning for heavy machinery systems. Yin's most impactful contribution — an RBF neural network-based adaptive sliding mode controller for electro-hydraulic servo systems — has garnered over 212 citations, reflecting its significance in addressing system uncertainties and nonlinearities. His 2017 work on GA-optimized PID control for robotic excavator trajectory tracking (160 citations) demonstrated early leadership in intelligent excavator automation. A recurring theme across his research is the precise characterization and compensation of nonlinear friction, a critical challenge in hydraulic systems, addressed through multiple studies totaling over 135 citations combined. Beyond low-level control, Yin has advanced multi-objective trajectory optimization, adaptive impedance control for contact-force regulation, and human-machine cooperative interfaces for excavators. His breadth — extending from humanoid robot stability in his earlier career to cutting-edge construction robotics — underscores a versatile and enduring research vision that continues to shape intelligent heavy equipment automation.
Research Focus
Key Achievements
Top Papers
- 1
- 2Robotic excavator trajectory control using an improved GA based PID controller160 citations · 2017
- 3Parameters identification and trajectory control for a hydraulic system88 citations · 2019
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- 7Flexible virtual fixtures for human-excavator cooperative system28 citations · 2019
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