Kouhei Ito
Papers
1
Total Citations
4
H-Index
1
About
Kouhei Ito is a researcher whose work centers on control systems, estimation theory, and their practical applications in robotics. His key contributions lie in the development of advanced state and disturbance estimation methods, particularly those grounded in the Internal Model Control (IMC) structure. In his most cited work, "State and Disturbance Estimation Based on Internal Model Control Structure and Its Application to Sensorless Grasping Control" (2007), Ito proposed a novel controller scheme that leverages an inverse or approximate inverse system within the IMC framework. While this approach offers theoretical elegance, it also introduces a significant practical challenge: the resulting controller is often of high order, making it cumbersome for real-world implementation. This tension between theoretical rigor and practical feasibility is a central theme in his research. Though his citation counts are modest—with his top paper garnering 4 citations—Ito's work is valued for its foundational insights into sensorless control, particularly for robotic grasping tasks where direct sensing is difficult. His research continues to influence engineers seeking to bridge the gap between sophisticated control theory and deployable, low-order solutions.
Research Focus
Key Achievements
Top Papers
- 1