Zhongqiang Pan
Zhejiang University, Jiangsu University of Science and Technology
Papers
2
Total Citations
44
H-Index
2
About
Zhongqiang Pan is a leading researcher in rehabilitation robotics and human–robot cooperative control, with a focus on developing intelligent, data-driven systems for lower extremity exoskeletons. His work bridges the gap between advanced control theory and practical assistive technologies, aiming to enhance mobility and quality of life for individuals with motor impairments. Pan’s most cited paper (2016, 40 citations) introduces a non-linear sliding mode controller that integrates radial basis function neural networks to model human–machine interaction, significantly improving tracking performance while reducing interaction forces—a critical step toward seamless human–robot cooperation. More recently, he pioneered the interval type-2 intuition fuzzy brain emotional learning network (2021), a model-free control approach that relies solely on input-output data, eliminating the need for exact dynamic models in rehabilitation robots. This innovation represents a paradigm shift toward adaptive, computationally efficient control for complex, multi-degree-of-freedom systems. By combining neural networks, fuzzy logic, and emotional learning, Pan’s contributions are shaping the next generation of intuitive, responsive exoskeletons, with potential applications in physical therapy, assistive mobility, and human augmentation.
Research Focus
Key Achievements
Top Papers
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- 2