Kuan-Yun Hsieh

Papers

Total Citations

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About

Kuan-Yun Hsieh is a researcher specializing in intelligent control systems, robotics, and computational intelligence, with a particular focus on applying advanced learning architectures to real-world motion control challenges. His work centers on the development of sophisticated control frameworks for robot manipulators, leveraging the complementary strengths of fuzzy logic and neural networks to achieve high-precision, adaptive performance in complex, nonlinear systems. Hsieh's most notable contribution is his 2003 paper introducing a Robust Fuzzy-Neural-Network (RFNN) control system for tracking control of n-link robot manipulators, developed through a backstepping design procedure and validated via computer simulations of a three-link SCARA robot manipulator. This work has garnered 12 citations and represents a meaningful advance in bridging theoretical control design with practical robotic applications. Building on this foundation, his 2004 research explored intelligent optimal control systems, employing fuzzy neural network controllers to approximate nonlinear functions within optimal control laws, further extending the applicability of hybrid intelligent methods to robotic tracking tasks. While Hsieh's citation record reflects an emerging body of work, his contributions offer valuable methodological groundwork for researchers pursuing robust, learning-based solutions in robotic manipulation and intelligent automation systems.