Honghai Ji
Papers
2
Total Citations
14
H-Index
2
About
Honghai Ji is a researcher at the forefront of intelligent control systems, specializing in model-free adaptive control (MFAC) and its application to robotics. His work addresses critical challenges in real-world automation, particularly for wheeled and humanoid robots operating under imperfect conditions. Ji’s major contributions include the development of a data learning-based MFAC method that integrates locally weighted regression, successfully applied to path-tracking control for an NAO robot—a key achievement in humanoid robotics. He has also pioneered an improved MFAC algorithm with data compensation to handle time delays and data dropout in two-wheeled balancing vehicles, advancing robust attitude control. With his most-cited paper garnering 11 citations and his 2025 work already attracting attention, Ji’s research is gaining recognition for its practical impact. His innovations bridge the gap between theoretical control methods and real-world robotic systems, making his work essential reading for students and researchers in adaptive control, robotics, and cyber-physical systems.
Research Focus
Key Achievements
Top Papers
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