Jun-Zhou Yue
Papers
1
Total Citations
3
H-Index
1
About
Dr. Jun-Zhou Yue is a control theorist whose work centers on iterative learning control (ILC) and adaptive systems for discrete-time dynamics. His most significant contribution addresses a fundamental challenge in precision control: how to handle systems with unknown high-order internal models (HOIMs). In his 2016 paper, Dr. Yue introduced an online identification method that enables ILC to converge even when the internal models governing initial states and external disturbances are unknown—a critical advance for repetitive manufacturing and robotic tasks. This work, cited 3 times, provides a rigorous framework for systems where reference trajectories are generated by known HOIMs but the plant dynamics remain partially opaque. Dr. Yue’s research bridges theoretical control design with practical implementation, offering engineers a systematic approach to improving performance in iterative tasks without requiring full system knowledge. His contributions are particularly valuable for applications in precision motion control and industrial automation, where repetitive operations demand both accuracy and adaptability. By tackling the interplay between known and unknown dynamics, Dr. Yue continues to advance the frontiers of learning-based control for discrete-time systems.
Research Focus
Key Achievements
Top Papers
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