Xiangkui Jiang
Papers
2
Total Citations
11
H-Index
2
About
Xiangkui Jiang’s research centers on intelligent control systems for robotic manipulators, with a particular focus on fuzzy logic and decentralized adaptive control. Their major contributions lie in developing novel fuzzy adaptation algorithms that address uncertainty modeling errors in robot manipulator systems, enhancing stability and performance in complex operational environments. Jiang’s most cited work, “Fuzzy Adaptation Algorithms’ Control for Robot Manipulators with Uncertainty Modelling Errors” (2018), has garnered 9 citations and introduces an adjustable parameter in fuzzy logic systems to improve reference model dynamic tracking. This work demonstrates a practical approach to handling nonlinear uncertainties that plague real-world robotic applications. In their 2019 study on decentralized fuzzy linguistic control, Jiang explored how human linguistic expressions—expert words and sentences—can be translated into control actions via membership functions, enabling multiple robotic manipulators to coordinate with guaranteed global stability. This human-inspired approach bridges the gap between natural language and machine control, offering intuitive frameworks for multi-robot systems. While Jiang’s citation counts are modest, their work represents foundational steps toward more adaptive, human-like robotic control, particularly valuable for researchers exploring fuzzy systems, decentralized coordination, and human-robot interaction in manufacturing and service robotics.
Research Focus
Key Achievements
Top Papers
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- 2