Youqing Wang

Tsinghua University, Shandong University of Science and Technology, Beijing University of Chemical Technology

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About

Dr. Youqing Wang is a leading researcher in nonlinear systems control, fault diagnosis, and iterative learning control (ILC). His work addresses critical challenges in system reliability and energy optimization. Notably, his 2006 paper on sensor gain fault diagnosis for nonlinear systems has garnered 24 citations, establishing foundational methods for detecting and isolating faults in complex dynamic systems. Dr. Wang has also made significant contributions to point-to-point ILC, as demonstrated by his 2019 study on energy-optimal time allocation for specified output tracking (17 citations). This work innovatively treats time allocation as an optimization variable to minimize control energy, a departure from conventional fixed-time approaches. Most recently, his 2025 paper introduces adaptive global predefined-time control for robotic systems using multiple multidimensional Taylor networks, achieving output constraint satisfaction with only 4 citations to date but representing a cutting-edge advance in robotic precision control. Dr. Wang’s research bridges theoretical rigor with practical applications, offering impactful solutions for autonomous systems, manufacturing, and robotics. His work continues to inspire new directions in control theory and fault-tolerant design.