Bing Cui
Papers
2
Total Citations
10
H-Index
2
About
Bing Cui is a rising scholar in nonlinear control theory, with a focus on adaptive and neuroadaptive control for uncertain nonlinear systems and multi-agent networks. His work addresses critical challenges in achieving precise, time-constrained tracking and consensus under uncertainties, disturbances, and output constraints. Cui’s most cited paper (2024, 8 citations) introduces a fixed-time neuroadaptive backstepping approach with predictor-based learning, enabling robust tracking for uncertain nonlinear systems within a predetermined settling time. His 2025 work (2 citations) advances prescribed-time consensus control for high-order nonlinear multi-agent systems with output constraints, employing a bounded time-varying gain method to ensure safety and performance. These contributions are significant for applications in robotics, autonomous vehicles, and cooperative systems where reliability and timing are paramount. Cui’s research is gaining traction for its innovative fusion of neural approximation, adaptive learning, and fixed/prescribed-time frameworks, offering practical solutions to complex real-world control problems.
Research Focus
Key Achievements
Top Papers
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