Che-Pin Kuo

Papers

Total Citations

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About

Che-Pin Kuo is a researcher specializing in advanced fuzzy control systems and their application to robotic dynamics. His work focuses on designing robust controllers for complex mechanical systems, particularly two-link arm robots and inverted pendulum robots. Kuo’s major contributions include developing stabilization conditions for fuzzy controllers using Linear Parameter Varying (LPV) Takagi-Sugeno (T-S) fuzzy models, which address stochastic behaviors in systems with movable supportive bases. He also pioneered the use of Imperfect Premise Matching (IPM) in fuzzy controller design for discrete-time inverted pendulum robot systems, offering a novel approach to simulating human stance and balance. While his most-cited papers have garnered modest citation counts (3 and 2 citations respectively), they represent foundational work in applying T-S fuzzy models to real-world robotic challenges. Kuo’s research bridges theoretical control engineering and practical robotics, with potential implications for humanoid robot stability and assistive technologies. His contributions to LPV-based fuzzy control and IPM techniques continue to inform emerging studies in nonlinear system control and robotic locomotion.