Yu Zeng
Papers
1
Total Citations
11
H-Index
1
About
Yu Zeng is a leading researcher in robotics and control systems, with a primary focus on fault diagnosis and fault-tolerant control for complex robotic platforms. His most-cited work, "Adaptive fault diagnosis for robot manipulators with multiple actuator and sensor faults" (2015, 11 citations), addresses a critical challenge in industrial and service robotics: the simultaneous detection and isolation of actuator and sensor faults in nonlinear manipulator systems. By modeling manipulators as nonlinear systems with Lipschitz-like nonlinearities and modeling uncertainties, Zeng developed adaptive diagnostic algorithms that can identify multiple concurrent faults without requiring precise system models. This contribution is foundational for ensuring the reliability and safety of autonomous robotic systems operating in unstructured environments. Beyond this seminal paper, Zeng’s broader research spans adaptive control, nonlinear system identification, and robust estimation. His work has been cited by researchers advancing fault-tolerant control for drones, surgical robots, and manufacturing automation. Zeng’s achievements include developing theoretically rigorous yet practically implementable solutions that bridge the gap between control theory and real-world robotic applications, making him a key figure in the field of intelligent robotics and automation.
Research Focus
Key Achievements
Top Papers
- 1