Jiangfei Ji
Papers
2
Total Citations
19
H-Index
2
About
Dr. Jiangfei Ji is a robotics researcher whose work focuses on intelligent control systems for robotic manipulators, particularly in uncalibrated and disturbance-prone environments. His key research areas include nonlinear control, visual servoing, and machine learning integration for robotics. Dr. Ji’s major contributions lie in developing robust control frameworks that combine adaptive extreme learning machines (ELM) with sliding mode control and Kalman filter optimization to address critical challenges in robotic manipulation—such as external disturbances, system noise, and slow convergence. His 2022 paper on nonlinear integral sliding mode control with adaptive ELM has garnered 10 citations, while his work on Kalman filter-optimized ELM and fuzzy logic for visual servoing has received 9 citations. These studies are notable for tackling real-world problems in uncalibrated visual servoing systems, including perturbation noises and error statistics. Dr. Ji’s research advances the reliability and precision of robotic manipulators in dynamic environments, making his work valuable for students and researchers in robotics, control theory, and intelligent systems.
Research Focus
Key Achievements
Top Papers
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- 2