Yuantao Yu
Papers
2
Total Citations
135
H-Index
2
About
Yuantao Yu is a leading researcher in the field of robotics and control systems, with a primary focus on robust model predictive control (MPC) for robot manipulators operating under disturbances. His work addresses critical challenges in trajectory tracking, specifically when robotic systems are subject to joint state constraints and input torque limits. Yu’s major contribution lies in the development of tube-based robust MPC algorithms, which effectively bound the effects of external disturbances to ensure stable and precise control. His 2020 paper, "Robust Model Predictive Tracking Control for Robot Manipulators With Disturbances," has garnered 132 citations, underscoring its influence on the design of resilient robotic systems. This work is widely recognized for advancing the practical application of MPC in real-world environments where disturbances are unavoidable. Yu’s research is essential reading for students and engineers working on autonomous robotics, nonlinear control, and disturbance rejection. His continued efforts in refining robust control strategies are shaping the next generation of safe and efficient robotic manipulators.
Research Focus
Key Achievements
Top Papers
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