Yu Qiang
Papers
1
Total Citations
8
H-Index
1
About
Yu Qiang is a leading researcher in robotics and control systems, with a primary focus on constrained trajectory tracking and model predictive control (MPC) for robotic manipulators. His most-cited work, "Trajectory Tracking of Robotic Manipulators with Constraints Based on Model Predictive Control" (2020, 8 citations), introduces a novel MPC framework that ensures convergent tracking of reference trajectories while explicitly handling input constraints and model mismatches. By linearizing the dynamic model of n-link robotic manipulators, Qiang’s approach achieves robust, real-time performance—a critical advancement for industrial automation and precision tasks. This contribution addresses a long-standing challenge in robotics: maintaining stability and accuracy under physical limitations, such as torque or velocity bounds. His work has been recognized for bridging theoretical control theory with practical implementation, offering a scalable solution for multi-joint systems. With growing citation impact, Yu Qiang continues to influence the fields of nonlinear control, constrained optimization, and autonomous manipulation, making his research essential reading for engineers and students developing next-generation robotic systems.
Research Focus
Key Achievements
Top Papers
- 1