Papers
6
Total Citations
145
H-Index
4
About
Dr. Jinliang Ding is a leading researcher in intelligent control and robotics, with a focus on fault-tolerant systems and adaptive control for mobile and legged robots. His work addresses critical challenges in ensuring safe and robust operation under actuator failures and dynamic uncertainties. A standout contribution is his 2024 paper on "Fault-Tolerant Prescribed Performance Control of Wheeled Mobile Robots," which has garnered 106 citations, introducing a mixed-gain adaptation approach to maintain trajectory tracking despite partial loss of wheel actuation. Dr. Ding has also pioneered optimal control strategies, such as using adaptive dynamic programming for moving-target circumnavigation by multiple wheeled mobile robots (13 citations), and developed the FT-CPG framework for fault-tolerant quadruped locomotion under multi-joint failures. His recent innovations include sample-efficient reinforcement learning and observer-driven temporal graph convolutional networks for early fault detection in control systems. Through these works, Dr. Ding has made significant impacts on autonomous navigation, robot resilience, and intelligent control theory, establishing himself as a key figure in advancing reliable, high-performance robotic systems for real-world applications.
Research Focus
Key Achievements
Top Papers
- 1
- 2Sample-efficient backtrack temporal difference deep reinforcement learning18 citations · 2025
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- 5Guest Editorial2 citations · 2016
- 6