Xiaojun Ban
Papers
2
Total Citations
16
H-Index
2
About
Xiaojun Ban is a leading researcher in the control of complex, nonlinear mechanical systems, with a particular focus on fuzzy logic control and underactuated robotics. His work addresses the fundamental challenge of achieving precise, stable control in systems that are inherently difficult to manage due to high nonlinearity or limited actuation. Ban’s most notable contribution is his pioneering application of type-2 fuzzy logic control to underactuated truss-like robotic fingers (UTRF), a complex system that mimics human dexterity. His 2017 paper on this topic, which has garnered 13 citations, established a new benchmark by demonstrating superior performance over traditional type-1 fuzzy controllers. Further advancing the field, Ban developed a novel framework for perfect tracking control in discrete-time Takagi–Sugeno (TS) fuzzy systems using feedback linearization, a critical requirement for high-precision applications like robotic control. Though his citation counts are still growing, his work is foundational for researchers tackling the intersection of fuzzy systems and underactuated mechanics, offering a systematic pathway from theory to robust, real-world control solutions.
Research Focus
Key Achievements
Top Papers
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