Qinruo Wang
Papers
4
Total Citations
52
H-Index
3
About
Qinruo Wang is a control systems and robotics researcher whose work focuses on adaptive control, intelligent systems, and robotic dynamics. Their key research areas include type-2 fuzzy control, event-triggered control for robotic manipulators, and neural network-based parameter identification for industrial robots. Wang’s most cited work, “Fire-rule-based direct adaptive type-2 fuzzy H∞ tracking control” (2011, 28 citations), introduced a novel approach to robust tracking control under uncertainty. More recently, their 2023 paper on adaptive prescribed settling time control for uncertain robotic manipulators (17 citations) addresses critical challenges in state-constrained systems. Wang has also contributed to industrial robotics through dynamic parameter identification using radial basis function neural networks (RBFNNs), improving model accuracy for large inertia robots. Additional work includes motion planning for single-legged robots using center-of-pressure dynamics. While their citation counts reflect a developing career, Wang’s research demonstrates a clear trajectory toward practical, constraint-aware control solutions for complex robotic systems, bridging theoretical control methods with real-world industrial applications.
Research Focus
Key Achievements
Top Papers
- 1Fire-rule-based direct adaptive type-2 fuzzy H∞ tracking control28 citations · 2011
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