Zhonghua Wu
Papers
6
Total Citations
129
H-Index
5
About
Zhonghua Wu is a control systems researcher whose work spans networked control under cyber-physical threats and advanced robotic manipulator control. His most influential contribution, "Resilient Model-Free Adaptive Iterative Learning Control for Nonlinear Systems Under Periodic DoS Attacks via a Fading Channel" (2021, 102 citations), addresses a critical challenge in modern networked systems: maintaining robust control performance when communications are compromised by denial-of-service attacks and fading channel phenomena. This work demonstrates Wu's ability to bridge theoretical control design with real-world security concerns in cyber-physical systems. More recently, Wu has directed his expertise toward robotic manipulator trajectory tracking, developing innovative prescribed performance and predefined-time control frameworks. His contributions in non-fragile prescribed performance control are particularly noteworthy, tackling the practical fragility limitations inherent in conventional control strategies while guaranteeing both transient and steady-state error bounds — without relying on function approximation techniques. His 2025 publications further extend these ideas through fault-tolerant and disturbance observer-based designs, underscoring his commitment to robust, reliable robotic systems. Collectively, Wu's body of work reflects a researcher who consistently advances control theory to meet demanding real-world challenges in security, reliability, and precision performance.
Research Focus
Key Achievements
Top Papers
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