Yuchen Wu

University of Electronic Science and Technology of China, University of Michigan–Ann Arbor

Papers

Total Citations

H-Index

About

Yuchen Wu is a rising researcher at the forefront of intelligent robotic control and advanced manufacturing, whose work bridges the gap between theoretical precision and real-world industrial reliability. Their primary research areas encompass model predictive control (MPC), nonlinear sliding mode control (NNSMC), and closed-loop additive manufacturing (AM) systems. In their most cited work, "A novel MPC-NNSMC composite control method for robotic manipulators considering uncertainties and constraints" (2025, 7 citations), Wu introduced a hybrid control framework that robustly handles dynamic uncertainties and physical constraints—a critical advancement for high-precision robotic operations in unstructured environments. This contribution has already garnered attention for its potential to enhance safety and performance in autonomous manufacturing cells. Wu’s earlier landmark paper, "Toward Closed-Loop Additive Manufacturing: Paradigm Shift in Fabrication, Inspection, and Repair" (2023, 3 citations), proposed a transformative vision for integrating real-time sensing and feedback control into 3D printing processes, addressing the long-standing challenge of process unreliability due to stochastic material behaviors. This forward-looking work has helped catalyze a paradigm shift toward self-correcting, quality-assured AM systems. With a growing citation record and a focus on solving practical constraints in robotics and fabrication, Yuchen Wu is establishing themselves as a key innovator in the next generation of intelligent, closed-loop manufacturing technologies.