Deniz Tan
Papers
1
Total Citations
6
H-Index
1
About
Deniz Tan is a control systems researcher whose work focuses on the modeling and stabilization of complex, underactuated mechanical systems. His most cited paper, "Classical and intelligent methods in model extraction and stabilization of a dual-axis reaction wheel pendulum: A comparative study" (2022, 6 citations), tackles the challenge of controlling an open-loop unstable dual-axis reaction wheel pendulum (DA-RWP). Tan’s major contribution lies in his rigorous approach: first deriving both nonlinear and linear models using Lagrangian energy methods, then applying a comparative framework of classical and intelligent control strategies to achieve stabilization. This work is notable for bridging theoretical modeling with practical control implementation, offering insights for robotics and aerospace applications where underactuated dynamics are common. Though early in his career, Tan’s systematic methodology and focus on comparative analysis provide a valuable foundation for researchers exploring advanced control of unstable systems. His research demonstrates a commitment to solving real-world stabilization problems through a blend of analytical modeling and intelligent algorithms.
Research Focus
Key Achievements
Top Papers
- 1