Qingqun Mai
Papers
2
Total Citations
7
H-Index
2
About
Qingqun Mai is a rising researcher in the field of multi-robot systems, with a focus on advanced cooperative control strategies. Their work centers on developing predefined-time control frameworks that guarantee system convergence within a user-specified time, independent of initial conditions—a critical advancement for time-critical applications like search-and-rescue and autonomous swarms. Mai’s key contributions include integrating adaptive fuzzy logic and event-triggered mechanisms to handle external disturbances, input saturation, and model uncertainties, as demonstrated in their 2023 paper on adaptive fuzzy event-triggered cooperative control (5 citations). They have also pioneered predefined-time H∞ cooperative control with adjustable prescribed performance functions and adaptive command filters (2025, 2 citations), enhancing robustness and tracking precision. By combining Lyapunov-based design with practical constraints, Mai’s work bridges theoretical guarantees and real-world implementation, offering scalable solutions for multi-agent coordination. Their research is gaining traction for addressing fundamental challenges in nonlinear, uncertain environments, making it highly relevant for students and engineers working on autonomous systems, distributed control, and cyber-physical networks.
Research Focus
Key Achievements
Top Papers
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- 2