Papers
3
Total Citations
13
H-Index
2
About
Bao Shi is a researcher specializing in intelligent control systems, fuzzy logic, and robotics, with a particular focus on two-wheeled self-balancing robots. Their major contributions lie in developing advanced control methodologies that enhance the stability and performance of complex robotic systems. Notably, Shi’s work on the GOOGOL two-wheeled self-balancing robot introduced a variable universe type-II fuzzy logic control design, leveraging linear parameter varying techniques and linear matrix inequalities to solve control challenges—a paper that has garnered 6 citations. Further extending this line of research, Shi proposed a tensor product model transformation-based control method with non-fixed-time step sampling, addressing dimensionality issues in high-dimensional models. In 2024, Shi advanced the field with a self-organizing hierarchical incremental learning framework based on stochastic configuration mechanisms, demonstrating universal approximation capabilities. With a growing citation impact, Bao Shi’s innovative approaches to fuzzy control and adaptive learning are paving the way for more efficient, scalable robotic systems, making their work essential reading for students and researchers in control theory and robotics.
Research Focus
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