Kuan‐Hua Chen
Papers
1
Total Citations
5
H-Index
1
About
Kuan-Hua Chen is a researcher whose work bridges intelligent control systems and robotics, with a particular focus on two-wheeled mobile robots. His most-cited paper, "Motion controller design for two-wheeled robot based on a batch learning structure" (2008), introduces a novel learning architecture that integrates a fuzzy inference system with a Genetic Algorithm (GA) to automatically design motion controllers. This work stands out for its three-state batch learning process—control, system identification, and controller refinement—which enables the robot to adapt and optimize its motion in real-time without manual tuning. While his citation count (5) reflects a niche but specialized impact, Chen’s contribution is significant in advancing autonomous control for unstable, two-wheeled platforms, a challenging area in robotics. His approach offers a practical framework for self-tuning controllers, reducing reliance on human expertise and enhancing robot adaptability. For students and researchers in robotics and control systems, Chen’s work provides a clear example of how evolutionary algorithms and fuzzy logic can be combined to solve real-world motion control problems, making it a valuable reference for those exploring intelligent, learning-based robotic systems.
Research Focus
Key Achievements
Top Papers
- 1