Sharina Huang
Papers
1
Total Citations
2
H-Index
1
About
Sharina Huang is a control systems researcher whose work focuses on the stabilization and control of complex, nonlinear robotic platforms. Her primary research areas include tensor product (TP) model transformation, parallel distributed compensation (PDC), and the real-time control of underactuated systems, with a particular emphasis on two-wheeled self-balancing robots. Huang’s most notable contribution is her 2021 study on the GOOGOL mobile two-wheeled self-balancing robot, where she applied a TP model transformation-based PDC control method with a non-fixed-time step sampling approach. This work critically addresses a key limitation in high-dimensional linear variable parameter (LVP) models—the exponential increase in computational burden as dimensionality grows—by proposing a more efficient sampling strategy. While her paper has garnered 2 citations to date, its significance lies in identifying and tackling a fundamental bottleneck that restricts the practical deployment of TP-based controllers in real-time applications. Huang’s research is particularly valuable for engineers and roboticists seeking to balance computational feasibility with robust control performance in autonomous mobile systems.
Research Focus
Key Achievements
Top Papers
- 1