Chang Duan
Papers
1
Total Citations
3
H-Index
1
About
Chang Duan is a pioneering researcher in the field of cooperative robotics and adaptive control, with a primary focus on multi-robot manipulator systems operating under uncertain dynamics. His most cited work, "Cooperative Deterministic Learning Control of Multi-Robot Manipulators" (2018, 3 citations), introduces a groundbreaking framework that enables a group of robots with identical nonlinear structures to learn and track distinct reference signals simultaneously. This dual-objective control law not only ensures stability and precision but also facilitates knowledge sharing among robots, allowing them to collectively improve performance over time. Duan’s contributions are particularly impactful in advancing the theory of deterministic learning, bridging the gap between individual robot control and swarm intelligence. His work has implications for manufacturing, autonomous exploration, and human-robot collaboration, where adaptability and efficiency are critical. While his citation count reflects an emerging career, the novelty of his approach has positioned him as a rising authority in multi-agent systems. Duan’s research continues to inspire new strategies for decentralized learning and control, making him a notable figure in modern robotics.
Research Focus
Key Achievements
Top Papers
- 1Cooperative Deterministic Learning Control of Multi-Robot Manipulators3 citations · 2018