Young-Chang Kang

Papers

Total Citations

H-Index

About

Dr. Young-Chang Kang is a leading researcher in intelligent robotic control systems, specializing in advanced fuzzy logic and sliding mode control methodologies. His work primarily focuses on enhancing the autonomy and safety of mobile robots and manipulators through sophisticated obstacle avoidance and robust motion control. Dr. Kang’s major contributions include the development of an advanced fuzzy potential field method for mobile robot obstacle avoidance, which integrates fuzzy control logic to dynamically manage repulsive forces, significantly improving navigation in complex environments. This seminal work has garnered 29 citations, underscoring its impact on the field. Additionally, he pioneered the advanced interval type-2 fuzzy sliding mode control (AIT2FSMC) for robot manipulators, a hybrid approach that combines interval type-2 fuzzy systems with sliding mode control to emulate feedback linearization laws, achieving superior robustness against uncertainties. With 10 citations, this work highlights his innovative integration of fuzzy logic and control theory. Dr. Kang’s research not only advances theoretical frameworks but also offers practical solutions for real-world robotic applications, making him a notable figure in intelligent systems engineering.