Kiyonori Inaba
Papers
2
Total Citations
17
H-Index
2
About
Kiyonori Inaba is a researcher whose work bridges control theory and robotics, with a focus on iterative learning control (ILC) and intelligent collaborative systems. His most cited paper, "Design of iterative learning controller based on frequency domain linear matrix inequality" (2009, 12 citations), introduces a novel ILC design method that leverages frequency domain linear matrix inequalities (LMIs) to address the computational challenges of lifted system representations—a key advancement for improving precision in repetitive tasks. This work demonstrates his ability to refine theoretical frameworks for practical control applications. More recently, Inaba has explored the frontier of human-robot interaction through his 2023 paper "Intelligent and Collaborative Robots" (5 citations), which examines how robots can work alongside humans in shared environments. His contributions are particularly relevant for students and researchers interested in control systems, optimization, and the growing field of collaborative robotics, offering insights into both foundational control theory and emerging applications in intelligent automation.
Research Focus
Key Achievements
Top Papers
- 1
- 2Intelligent and Collaborative Robots5 citations · 2023