Jian-Xin Xu

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About

Jian-Xin Xu is a pioneering researcher in the fields of biomimetic robotics and advanced control systems, with a particular focus on robotic fish locomotion and iterative learning control. His most impactful work centers on the modeling and control of multi-joint biomimetic robotic fish, where he developed analytical control designs using Lagrangian dynamics to achieve realistic Anguilliform swimming motions. A major contribution is his biomimetic learning approach, which employs a General Internal Model (GIM) to enable robotic fish to learn coordinated locomotion directly from observing live fish—a breakthrough that allows for scalable and adaptive swimming behaviors without manual programming. His foundational work on iterative learning control for robotic manipulators introduced a hybrid strategy combining memory-based control with current-cycle feedback, advancing the field of repetitive motion control. With over 12 citations on his leading robotic fish paper and 8 on his biomimetic learning study, Xu’s research has significantly influenced the design of autonomous underwater vehicles. His work bridges theoretical control engineering with biological inspiration, offering practical solutions for agile, fish-like robots capable of operating in complex aquatic environments.