Haiping Zhu

Papers

Total Citations

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About

Haiping Zhu is a researcher whose work bridges intelligent control systems and smart city technologies, with a particular focus on multi-object tracking and adaptive robotics. Zhu’s most cited paper, “Multi-object tracking based on attention networks for Smart City system” (2022, 11 citations), advances the application of deep attention mechanisms to track multiple objects in complex urban environments, a critical capability for surveillance, traffic management, and autonomous systems. Earlier foundational work, “Adaptive Control for Robotic Manipulators base on RBF Neural Network” (2013, 5 citations), introduced a novel adaptive neural network controller that combines PD feedback with a dynamic compensator—integrating radial basis function neural networks and variable structure control—to solve trajectory tracking problems for robotic manipulators under uncertainty. This contribution addresses a longstanding challenge in robotics: maintaining precise control despite unknown dynamics and disturbances. Zhu’s research demonstrates a clear trajectory from foundational control theory to applied AI in smart infrastructure, making notable strides in both theoretical robustness and real-world deployment. With a growing citation footprint, Zhu’s work continues to influence researchers in robotics, neural control, and intelligent urban systems.