Hyuk Mo An
Papers
2
Total Citations
4
H-Index
2
About
Hyuk Mo An is a rising researcher in the field of advanced robotics control, with a primary focus on adaptive sliding mode control for robotic manipulators. His work addresses the critical challenge of managing model uncertainties and external disturbances inherent in robotic dynamic systems. An’s major contributions include the development of novel adaptive laws based on quasi-convex functions, which intelligently adjust control gains to enhance system robustness and performance. In his 2024 paper, he introduced an adaptive sliding mode control (ASMC) scheme that leverages quasi-convex functions and average sliding variables, while his 2025 study advanced this concept by integrating neural network-assisted time-delay estimation (TDE) to compensate for estimation errors. Though his most-cited works currently hold 2 citations each, they represent foundational steps toward more intelligent and resilient robotic control systems. An’s innovative combination of quasi-convex functions, neural networks, and sliding mode theory marks him as a promising contributor to the evolution of autonomous robotic manipulation, with potential applications in industrial automation and precision robotics.
Research Focus
Key Achievements
Top Papers
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- 2