Yi-Min Zheng
Papers
1
Total Citations
33
H-Index
1
About
Dr. Yi-Min Zheng is a leading researcher in intelligent robotic control systems, with a primary focus on adaptive control, nonlinear dynamics, and fuzzy neural network architectures. His most impactful work addresses the fundamental challenge of achieving precise tracking control for robot manipulators—systems characterized by high nonlinearity, strong coupling, and significant uncertainties from parameter disturbances and external interference. In his highly cited 2017 paper (33 citations), Dr. Zheng pioneered a robust adaptive Takagi-Sugeno-Kang (TSK) fuzzy cerebellar model articulation controller (CMAC) that effectively compensates for unmodeled dynamics and external disturbances. This innovative hybrid approach combines the learning capabilities of fuzzy logic with the structural advantages of cerebellar models, enabling manipulators to maintain stable, high-precision performance even under unpredictable operating conditions. His contributions have provided a practical framework for enhancing the reliability and adaptability of robotic systems in manufacturing, rehabilitation, and autonomous operations. Dr. Zheng’s work continues to influence the development of intelligent control strategies that bridge theoretical advances with real-world robotic applications.
Research Focus
Key Achievements
Top Papers
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