Chulyoung Jang

Papers

Total Citations

H-Index

About

Chulyoung Jang’s research lies at the intersection of nonlinear control systems, neural networks, and robotics, with a particular focus on enhancing the adaptability and robustness of autonomous manipulators. His most-cited work, “Trajectory control of robotic manipulators using chaotic neural networks” (2002), introduces a novel direct adaptive control framework that leverages the intrinsic dynamics of chaotic neural networks—specifically their self-feedback and internal feedback loops—to manage the complex, highly nonlinear behaviors of robotic systems. This approach demonstrates how chaotic neural architectures can outperform conventional controllers in trajectory tracking and disturbance rejection, offering a more resilient solution for real-time robotic control. While his citation count (6) reflects a niche but specialized impact, Jang’s contribution is notable for pioneering the integration of chaos theory with neural adaptive control, a concept that has inspired subsequent research in nonlinear system identification and intelligent robotics. His work underscores a forward-thinking application of biologically inspired computing to engineering challenges, making it a valuable reference for students and researchers exploring advanced control strategies in robotics and dynamical systems.