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About

Wei Shuning is a leading researcher in robotics and intelligent control systems, with a primary focus on adaptive and learning-based control for robotic manipulators and autonomous mobile robots. His most influential work, an adaptive iterative learning control (AILC) strategy for robot manipulators in task space, has garnered 21 citations and introduces a novel PD controller with gain switching and a learning feedforward term to achieve precise trajectory tracking under iterative operations. Shuning has also made significant contributions to specialized robotics, including the development of wavelet neural network robust control for transmission line deicing robots, a critical application for preventing power network failures caused by ice coating. His innovative use of electromagnetism-like mechanisms for model predictive control in path-tracking of autonomous mobile robots, as well as Q-learning algorithms for obstacle-crossing policies in deicing robots, demonstrates a unique ability to merge bio-inspired optimization with real-time control challenges. With a publication record spanning from 2010 to 2014, Shuning’s work is characterized by practical solutions to high-dimensional, nonlinear problems—such as inverse kinematics—and a consistent emphasis on robustness in the presence of actuator saturations and external disturbances.