Zhongxing Ren

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About

Zhongxing Ren is a rising researcher in intelligent robotic control, specializing in advanced control strategies for multi-joint robotic arms and remotely operated manipulators. His work focuses on integrating neural networks, fuzzy logic, and active disturbance rejection techniques to enhance the precision, adaptability, and robustness of robotic systems operating in complex, real-world environments. Ren’s most-cited paper (2022, 16 citations) introduces a novel neuro PID controller for remotely operated robotic manipulators, addressing the critical need for intelligent control in industrial applications. He has also advanced fuzzy PID control for multi-joint robotic arms using hardware-in-loop schemes with Geomagic Touch haptic devices, and proposed an RBF neural network-based active disturbance rejection controller (2023) to improve attitude control under disturbances. Though early in his career, Ren’s work demonstrates a clear trajectory toward bridging theoretical control methods with practical robotic systems, with growing impact in the field of intelligent automation.