Zhankui Zeng
Papers
1
Total Citations
3
H-Index
1
About
Zhankui Zeng is a rising researcher in robotics and control systems, with a focus on continuum manipulators and intelligent neural network-based control. Their most-cited work, "Model-Less Tracking Control for Continuum Manipulators Based on Fuzzy Adaptive Zeroing Neural Networks" (2025), introduces a novel approach to controlling flexible, snake-like robotic arms without requiring precise mathematical models—a long-standing challenge in soft robotics. By integrating fuzzy logic with adaptive zeroing neural networks, Zeng’s method enhances tracking accuracy and robustness in dynamic environments, offering a practical solution for applications in minimally invasive surgery and industrial inspection. Though early in their career, this paper has already garnered 3 citations, signaling growing interest in their contributions. Zeng’s work bridges the gap between theoretical neural network design and real-world robotic control, demonstrating a talent for simplifying complex systems. Their research not only advances the field of continuum robotics but also provides a scalable framework for model-less control in other nonlinear systems. As a young innovator, Zeng is poised to make significant strides in intelligent automation and adaptive control.
Research Focus
Key Achievements
Top Papers
- 1