Tangzhong Song
Papers
16
Total Citations
208
H-Index
8
About
Tangzhong Song is a robotics and control systems researcher whose work sits at the intersection of advanced sliding mode control, model-free estimation, and robust manipulation. His research primarily addresses the persistent challenges of uncertainty, external disturbances, and imprecise dynamic modeling that complicate real-world robot control — problems with significant practical consequences in industrial and collaborative robotics. Song's most influential contribution, "Model-free finite-time terminal sliding mode control with a novel adaptive sliding mode observer" (2021, 61 citations), introduced a time delay estimation-based framework capable of handling impact-type disturbances that conventional methods struggle to manage. This work established a foundation for his broader research agenda: designing controllers that perform reliably without exact mathematical models of the system. Complementary studies explored funnel boundary constraints, prescribed performance criteria, and recursive terminal sliding mode architectures, collectively accumulating over 185 citations. Beyond control design, Song has made notable contributions to robot parameter identification, proposing physically feasible, friction-aware identification methods that improve real-world model accuracy. His more recent work on adaptive impedance control for contact force tracking with unknown environments signals a meaningful expansion toward human-robot interaction applications. Across his career, Song has consistently bridged theoretical rigor with practical deployability, making his work highly relevant for researchers tackling robust manipulation in unstructured settings.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
- 10