Papers
10
Total Citations
286
H-Index
8
About
Dr. Jun Ye is a leading researcher in intelligent control systems, mobile robotics, and multi-criteria decision-making under uncertainty. His most influential work focuses on adaptive and neural-network-based control for nonholonomic mobile robots, where he pioneered the integration of analog neural networks with backstepping and nonlinear PID techniques. His 2007 paper on adaptive control of nonlinear PID-based analog neural networks has garnered 112 citations, while his related work on tracking control using neural networks has accumulated 84 citations. Dr. Ye has also made significant contributions to the theory of fuzzy sets and decision-making, introducing the concept of intuitionistic fuzzy credibility sets (IFCS) to enhance reliability in performance evaluations—a method applied to industrial robots. His recent work on linguistic neutrosophic Z-number aggregation operators further advances decision-making under hybrid uncertainty. With over 280 total citations across his publications, Dr. Ye’s research bridges the gap between theoretical control algorithms and practical robotic applications, offering robust solutions for trajectory tracking, disturbance rejection, and spatial reasoning. His innovative use of compound cosine and sine function neural networks has set a benchmark for adaptive control in nonholonomic systems.
Research Focus
Key Achievements
Top Papers
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- 7Exploiting depth camera for 3D spatial relationship interpretation9 citations · 2013
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