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About

Yung-Hsiang Chen is a distinguished robotics and control systems researcher whose work centers on advanced motion control, trajectory tracking, and autonomous mobile robot systems. His research has made significant contributions to the development of nonlinear adaptive control frameworks, particularly leveraging fuzzy logic, sliding mode control, and optimal control theory to solve complex trajectory tracking challenges in wheeled mobile robots. Chen's most influential work, garnering 18 citations, introduced a nonlinear adaptive fuzzy control method exploiting skew symmetrical properties to simplify control design for wheeled mobile robots — a notable analytical breakthrough in the field. Building on this foundation, he has extended these methodologies to four-wheeled Mecanum platforms, swarm robotics systems optimized via H2 performance indices, and hybrid sliding mode strategies for autonomous mobile robots. His 2025 study on adaptive fuzzy hybrid sliding mode control, already accumulating 13 citations, underscores his continued influence on precision motion control research. Beyond theoretical contributions, Chen demonstrates a strong commitment to real-world implementation, evidenced by his practical work on autonomous robotic lawnmowers. Collectively, his publications reflect a researcher who bridges rigorous mathematical control theory with tangible engineering applications, making his work highly valuable to students and practitioners advancing the frontiers of intelligent autonomous systems.