Shuyou Yu

State Key Laboratory of Automotive Simulation and Control, Jilin University

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About

Shuyou Yu is a leading researcher in the field of nonlinear control systems, with a primary focus on model predictive control (MPC) and its application to robotics and mechatronics. His work centers on solving complex motion control problems, particularly path following and force regulation for wheeled mobile robots and robotic manipulators. Yu’s most influential contribution is his 2018 paper on MPC for path following of wheeled mobile robots, which has garnered 31 citations. In this work, he introduced a disturbance observer-based MPC framework that effectively estimates and compensates for input disturbances, significantly enhancing trajectory tracking accuracy under real-world uncertainties. He further extended this approach to robotic manipulators in his 2020 study on path following and terminal force control, where he integrated force regulation into the predictive control scheme—a critical advancement for tasks requiring both precise motion and contact force management. Yu has also made notable strides in robust control theory, developing an improved predictive control scheme for Lur’e systems using set-based learning to reduce conservatism in uncertain nonlinear environments. His research bridges theoretical rigor with practical implementation, offering scalable solutions for autonomous systems and industrial robotics.