Chang-Hyun Chai

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About

Chang-Hyun Chai is a robotics researcher whose work focuses on intelligent control systems for robotic manipulators and mobile robots. His key research areas include chaotic neural networks, fuzzy sliding-mode control, and precision motor control for robotic applications. Chai’s most notable contribution is his pioneering work on trajectory control of robotic manipulators using chaotic neural networks, which demonstrated robust characteristics for controlling highly nonlinear dynamic systems. This foundational paper has garnered 6 citations, establishing his early impact in the field. He further advanced mobile robotics by developing a trajectory tracking controller for two-wheeled mobile robots using a fuzzy sliding-mode controller based on hyperbolic functions, achieving robust attitude control under nonholonomic constraints. In precision motion control, Chai designed a stepper motor controller for robotic applications that enables independent and synchronized control of multiple motors using microstepping techniques, built around a 16-bit microprocessor for fast and reliable operations. His work bridges theoretical control methods with practical robotic implementations, contributing to the development of more adaptive and precise robotic systems.