Papers
10
Total Citations
133
H-Index
7
About
Chun-Fei Hsu is a leading researcher in intelligent control systems and robotics, with a primary focus on adaptive and neural-network-based control for nonlinear and unstable robotic platforms. His major contributions lie in developing advanced control architectures—such as recurrent wavelet neural networks (RWNN) and intelligent complementary sliding-mode control—that enable fast learning, robust performance, and fault tolerance in complex systems. Hsu’s work has been instrumental in the design and control of two-wheel self-balancing robots, wheeled bipedal robots, and unicycle robots, often integrating vision-based feedback and fuzzy logic for enhanced autonomy. His most cited paper, “Adaptive Control for MIMO Uncertain Nonlinear Systems Using Recurrent Wavelet Neural Network” (2012, 56 citations), demonstrates the power of RWNN in handling multi-input multi-output uncertainties. Other notable achievements include the vision-based line-following control of a two-wheel self-balancing robot (2018) and the implementation of a wheeled bipedal robot using fuzzy logic (2022). With over 130 total citations across his top works, Hsu’s research continues to push the boundaries of intelligent, dynamically stable robotic systems, making significant impacts on both theoretical control methods and practical robot applications.
Research Focus
Key Achievements
Top Papers
- 1
- 2Vision-Based Line-Following Control of a Two-Wheel Self-Balancing Robot17 citations · 2018
- 3
- 4Adaptive PI Hermite neural control for MIMO uncertain nonlinear systems11 citations · 2012
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- 7Motion planning and control of a picture-based drawing robot system8 citations · 2017
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