About

Maolin Jin is a leading researcher in advanced robot control systems, with particular expertise in time-delay estimation (TDE), sliding-mode control, and adaptive control strategies for robot manipulators. His work has fundamentally shaped how engineers approach model-free and robust control in robotics, earning him over 2,300 citations across his most influential publications alone. Jin's most celebrated contribution is his development and refinement of time-delay control (TDC) frameworks that eliminate the need for precise robot dynamic models — a longstanding practical challenge in robotics. His 2016 adaptive sliding-mode control scheme (524 citations) and 2009 nonsingular terminal sliding-mode work (422 citations) are landmark papers that combine TDE with advanced control architectures to achieve high-accuracy tracking with minimal chattering. His research spans compliant motion control, impedance control, flexible-joint humanoid robots, and nonlinear friction compensation, demonstrating remarkable breadth within the field. A consistent theme throughout Jin's career is bridging theoretical rigor with real-world applicability — designing controllers that are simultaneously simple, robust, and deployable on physical robotic systems. His 2019 work on adaptive gain dynamics further reflects his ongoing commitment to solving practical challenges such as significant payload variation. Jin's body of work represents an essential foundation for researchers and engineers advancing the next generation of intelligent robotic systems.

Research Focus

Key Achievements

20
H-Index
59
Papers
2,893
Total Citations
49
Avg Citations/Paper
🏆 Most Cited Paper
A New Adaptive Sliding-Mode Control Scheme for Application to Robot Manipulators
524 citations · 2016
📈 Most Prolific Year: 2022 (8 Papers)
🤝 Key Collaborators: 100
🏛 Institutions: Research Institute of Industrial Science and Technology, Korea Institute of Robot and Convergence, Korea Advanced Institute of Science and Technology, Harbin Institute of Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 33 days ago