Jingdong Zhang

Papers

Total Citations

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About

Jingdong Zhang is a researcher specializing in advanced control systems, particularly in the domain of teleoperation and bilateral servo control for robotic applications. His work focuses on enhancing the performance and stability of master-slave robotic systems used in hazardous or inaccessible environments, such as space, deep-sea exploration, and battlefield operations. Zhang’s most cited paper, “RBF neural network PID for Bilateral Servo Control System” (2013), introduces a novel force feedback bilateral servo system that leverages radial basis function (RBF) neural networks to optimize PID control parameters. This contribution addresses critical challenges in teleoperation, including system nonlinearities and time delays, enabling more precise and reliable remote manipulation. With 2 citations, this work has laid foundational insights for subsequent research in neural network-based adaptive control for hydraulic servo systems. Zhang’s research is pivotal for advancing human-robot interaction in extreme conditions, offering practical solutions for industries requiring high-stakes remote operations. His work continues to inspire innovations in intelligent control and telepresence technologies.