Guoli Ji

Papers

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About

Guoli Ji is a leading researcher in intelligent control systems, with a primary focus on robotic manipulator dynamics and adaptive fuzzy neural networks. His most cited work, "Robust Adaptive Tracking Control for Manipulators Based on a TSK Fuzzy Cerebellar Model Articulation Controller" (2017, 33 citations), addresses the fundamental challenge of controlling complex, nonlinear robotic systems plagued by parameter disturbances, external interference, and unmodeled dynamics. Ji’s major contribution lies in developing a robust adaptive control framework that integrates Takagi-Sugeno-Kang (TSK) fuzzy logic with cerebellar model articulation controllers (CMAC), enabling precise trajectory tracking despite system uncertainties. This innovative approach has significantly advanced the field of intelligent robotics by providing a computationally efficient and highly adaptive solution for multi-input, multi-output systems. With 33 citations, this paper has become a key reference for researchers working on nonlinear control and fuzzy systems. Ji’s work continues to influence the design of more resilient and autonomous robotic manipulators, making him a notable figure in the intersection of fuzzy logic, neural networks, and adaptive control theory.