Zhengtao Ding
Papers
15
Total Citations
449
H-Index
8
About
Zhengtao Ding is a leading researcher in autonomous systems, multi-robot coordination, and advanced control theory, whose work has significantly shaped how networked robotic systems are designed and analyzed. His research spans fixed-time and finite-time control, fault-tolerant coordination, bearing-based formation control, and reinforcement learning-driven optimization for complex nonlinear systems. Ding's most influential contribution, "Fixed-Time Formation Control of Multirobot Systems: Design and Experiments" (2018, 191 citations), tackled the critical challenge of time delays in vision-based multi-robot networks, demonstrating that timing guarantees can be achieved even under realistic communication constraints—a breakthrough with direct implications for search-and-rescue robotics. His subsequent work extended these ideas to unmanned aerial vehicle (UAV) swarms, addressing actuator faults and bearing-only sensing without reliance on global positioning. Complementing this, his explorations of fuzzy-model-based reinforcement learning and secure state estimation for nonlinear systems under cyberattacks highlight his breadth across control theory and cyber-physical security. With over 430 cumulative citations and contributions spanning multi-vehicle coordination, distributed Kalman filtering, and rigid shape formation, Ding's research bridges rigorous theoretical foundations with real-world experimental validation, making him an essential reference for students and engineers working at the frontier of intelligent autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1Fixed-Time Formation Control of Multirobot Systems: Design and Experiments191 citations · 2018
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- 5Distributed nonlinear Kalman filter with communication protocol29 citations · 2019
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