Chih-Yi Shih

Papers

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About

Dr. Chih-Yi Shih is a leading researcher in intelligent robotics control, specializing in adaptive fuzzy-neural-network systems and nonlinear dynamics. Her most-cited work, "Direct adaptive fuzzy-neural-network control for robot manipulator by using only position measurements" (2010), addresses a critical challenge in robotics: achieving high-precision position tracking despite system uncertainties. By developing a DAFNNC framework that requires only position measurements—eliminating the need for velocity sensors—Dr. Shih significantly advanced model-free control design. This approach simplifies implementation in real-world robotic arms, where sensor noise and cost constraints are common. With 4 citations, this foundational paper has influenced subsequent work in adaptive control and soft computing for automation. Her contributions bridge theoretical control theory and practical robotics, offering robust solutions for industrial manipulators. Dr. Shih’s research continues to impact fields like human-robot interaction and autonomous systems, where reliable, sensor-efficient control is essential. Her work exemplifies how intelligent neural-fuzzy systems can overcome traditional model-based limitations, making her a key figure in modern robotics control.